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Sybase IQ



Issue 1                                    Introduction
2012
                                           “Big Data” is the new hot topic for IT managers, and is causing quite a panic amongst some
                                           organizations; but, there is no need to panic, Big Data can be looked upon as Big Opportunity.
IN THIS ISSUE                              With the data explosion companies now have access to more information than ever before – if
                                           the data can be exploited properly it can lead to a big competitive advantage.
Introduction.........................1
                                           With companies acquiring massive amounts of data in different forms from different sources,
SAP Sybase IQ - Turning                    ranging from traditional channels with structured formats to social media channels with
Big Data into a Big                        unstructured formats, it has changed the focus of analytics in the “real-world”. Throughout
                                           organizations there are changes in the way data is being analyzed – in marketing, the focus has
Advantage............................. 2
                                           shifted to digital channels – click streams and social media – to understand buying patterns, and
Gartner Research:                          target marketing activities for maximum impact. In sales, the focus is on what we call “deal
Magic Quadrant for Data                    DNA”, to correlate emails, meeting notes and chatter to assess the probability that a sales
Warehouse Database                         deal will close. On the financial side, simulation is being used to predict margins and portfolio
                                           values; while on the operational side, machine data via sensors, and other kinds of digital data are
Management Systems......... 5
                                           being analyzed to track down operational inefficiencies – it’s no wonder companies are having
About Sybase..................... 29       information overload and are at a loss as to how to manage the information let alone how to use
                                           that information intelligently.

                                           The key to Big Data is the ability to access and connect all the data no matter what type or
                                           where it came from, in order to achieve this you have to break the information silos that trap
                                           data – turning massive amounts of data into actionable insight while providing complete access to
                                           decision makers – creating an environment that offers “intelligence for everyone”.




   Featuring research from
SAP Sybase IQ – Advanced                                  volume, variety and velocity of today’s                     Massive Scalability
Analytics Platform for                                    massive data needs and demands in a cost
                                                          effective and attainable manner.                            With a state of the art query processor
Big Data
                                                                                                                      Sybase IQ thrives on heavy ad hoc query
                                                          Sybase IQ is based on a three layer                         usages by large numbers of concurrent
SAP Sybase IQ is an analytic DBMS
                                                          architecture. A strong data management                      users – it’s designed to handle it. Built
designed specifically for advanced
                                                          layer is the foundation with a highly                       on PlexQ™ technology framework that
analytics, data warehousing, and business
                                                          compressed column store, and shared                         delivers a shared-everything massively
intelligence environments. Able to work
                                                          everything distributed MPP elastic cluster                  parallel processing (MPP) architecture
with massive volumes of structured and
                                                          that supports a variety of workloads and                    based on a columnar data store, it
unstructured data it is ideally suited to Big
                                                          active user community. The application                      delivers new levels of performance.
Data.
                                                          services layer sits above that to provide                   Unlike shared nothing solutions, a PlexQ
                                                          a variety of drivers, APIs, web services,                   grid dynamically manages analytics
Sybase IQ is built on an open, flexible
                                                          and federation capabilities to empower                      workloads across an easily expandable
column-store technology, unlike
                                                          developers. And wrapped around these                        grid of computing resources dedicated to
traditional relational databases, that store
                                                          two technology layers, is a rich ecosystem                  different groups and processes, making
data by row, slowly working through
                                                          of BI tools, partner libraries, packaged                    it simpler and more cost-effective to
each row of entire tables, clogging I/O
                                                          applications, and data integration tools                    support growing volumes of data and
channels, memory, and disk, Sybase IQ
                                                          to give you an end to end solutions. (See                   rapidly growing user communities.
uses a strategy called “vertical portioning”
                                                          Figure 1)
that stores data by column, reading only
the columns of data used by the query.                                                                                With PlexQ grid technology, enterprise
Using columns, not rows, delivers a 10 to                 Centralized Access to All                                   IT departments can more easily overcome
100 times performance boost compared                      Your Enterprise Data                                        the scalability limitations of traditional
to the traditional row-based approaches                                                                               data warehouses. Organizations are
– and Sybase IQ supports most of the                      Sybase IQ centralizes “Big Data” analysis                   now able to support user communities
popular hardware and OS configurations.                   of massive volumes of structured and                        across the enterprise, and integrate
                                                          unstructured data together using a                          analytics into business workflows. And,
Big Data is not new to Sybase. Sybase IQ                  wide range of advanced techniques                           it’s easy to leverage advanced analytics
has been building on the vision of a big                  and technologies – offering a data type                     within applications by using hundreds of
data analytics platform for several years                 agnostic engine Sybase IQ doesn’t care                      algorithms and data mining models that
now – the new Sybase IQ 15 family has                     what format of data you have or even                        can run inside Sybase IQ.
been a steady progression of releases                     where it came from. Whether it be                           Elastic computing of logical servers in the
that have followed a conscious roadmap,                   structured in a defined format, semi-                       PlexQ™ technology framework within
each one adding innovations that build                    structured available electronically,                        Sybase IQ allow IT staff to group together
upon the foundation and strengths of                      unstructured requiring text mining or                       compute resources, in a PlexQ grid, into
the previous release. Sybase IQ has been                  analytics tool extraction or web data,                      virtual groups in order to isolate the
designed to meet the growing needs of                     such as, social media – it simply doesn’t                   impact of different workloads and users
IT and Business Analysts to tame the                      matter with Sybase IQ.                                      from each other. When a user connects
                                                                                                                      to a logical server and runs a query, the




SAP Sybase IQ - Turning Big Data into a Big Advantage is published by Sybase. Editorial supplied by Sybase is independent of Gartner analysis. All Gartner research is ©
2012 by Gartner, Inc. All rights reserved. All Gartner materials are used with Gartner’s permission. The use or publication of Gartner research does not indicate Gartner’s
endorsement of Sybase’s products and/or strategies. Reproduction or distribution of this publication in any form without prior written permission is forbidden. The infor-
mation contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such
information. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed
herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services
and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in enti-
ties covered in Gartner research. Gartner’s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its
research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research,
see “Guiding Principles on Independence and Objectivity” on its website, http://www.gartner.com/technology/about/ombudsman/omb_guide2.jsp.




2
Figure 1: SAP Sybase IQ - A complete and comprehensive big data analytics platform
          Source: Sybase




query execution is only distributed to        For statistics and data mining Sybase IQ        techniques such as network analysis or for
member nodes of the logical server, and       supports a DBLytix library from Fuzzy           searching large amounts of unstructured
member nodes can be dynamically added         Logix containing hundreds of advanced           data that is not indexed.
or dropped as necessary.                      analytic, statistical and data mining
                                              algorithms that can run inside Sybase IQ.       In addition to a native MapReduce
Specialized Tools &                                                                           API, Sybase IQ offers four ways to
Techniques                                    For text analytics Sybase IQ provides           integrate results from 3rd party Hadoop
                                              comprehensive in-database text search           frameworks into Sybase IQ queries, giving
Sybase IQ has partnered with a number         capabilities. With Sybase IQ’s key              a tiered approach to analyzing massive
of key advanced analytic partners in          Analytics partnerships – both internal and      data sets. In essence, massive volumes
order to provide key in-database analytics    external, such as, SAP BusinessObjects,         of data can be searched from distributed
techniques. Using in-database analytics       ISYS and KAPOW, hundreds of document            file systems. The data returned from a
enterprises and application vendors can       formats and Web content can be ingested         Hadoop analysis can then be integrated
answer complex questions without having       and/or extracted into Sybase IQ for             into a Sybase IQ database in any of the
to move mountains of data to 3rd party        analysis.                                       four ways:
tools. With hundreds of statistical and                                                            • ETL Processing, which bulk load
data mining techniques, advanced text         Sybase IQ provides a native MapReduce                  data from Hadoop data stores into
analytics capabilities, and APIs to execute   API that can leverage massively parallel               Sybase IQ using the open source
proprietary algorithms safely inside          processing across a PlexQ™ grid. Using                 utility SCOOP from Sybase’s
Sybase IQ, companies can gain insights in     MapReduce allows you to move beyond                    partner Cloudera.
unparalleled time.                            limitations with SQL queries, enabling
                                                                                                   • Data Federation, which exposes
                                              you to more easily execute alternative
                                                                                                     HDFS files as tables in a Sybase IQ
                                                                                                     database that participate in SQL

                                                                                                                                     3
queries (HDFS files do not need to   to search and filter data for analysis in      movement can impose severe constraints
        be loaded into Sybase IQ).           combination with its column store engine.      on timely delivery of the results you
     •	 Query Federation, allowing SQL       Following the SQL Multimedia (SQL/             need to succeed and can account for up
        queries in Sybase IQ to execute      MM) standard for storing and accessing         to 75% of cycle time. By running analytic
        Hadoop processes that return data    geospatial data, Sybase IQ supports 2D         techniques inside the database Sybase
        that is incorporated into the SQL    geometries in the form of points, curves       IQ dramatically accelerates performance,
        result set, and finally.             (line strings and strings of circular arcs),   while avoiding governance and security
                                             and polygons. Sybase IQ also supports flat     concerns caused by data movement. You
    •	 Client-side Federation, which
                                             and round-Earth representations, allowing      need an analytics environment that can
        federates queries across Sybase
                                             you to choose the approach that best           analyze large volumes of data from diverse
        IQ databases and Hadoop files
                                             addresses your situation.                      sources and provide fast, accurate results
        using the TOAD© SQL tool from
                                                                                            - Sybase IQ’s in-database capabilities can
        Sybase’s partner Quest.
                                             Sybase IQ provides enterprises with APIs       give you this advantage.
                                             to create proprietary analytic algorithms
Use “R”, the popular open source
                                             that can run inside the Sybase IQ database     Successful Analytics Platform
statistical tool, to query Sybase IQ
                                             server for top performance. In particular,     for Big Data
databases using an RJDBC interface.
                                             Sybase IQ offers Java and C++ APIs, with
Furthermore, you can execute R libraries
                                             these APIs you can create User Defined       Sybase is on a mission to revolutionize Big
from Sybase IQ as a function call within
                                             Functions (UDFs) that are called through     Data Analytics with Sybase IQ. With our
SQL queries and return result sets.
                                             SQL queries. The UDFs can access all of      centralized data analysis delivering insights
                                             the data within a Sybase IQ database and     across your Enterprise, and our support
Sybase IQ also offers in-database
                                             can leverage a PlexQ™ grid for massively     of large user communities running a wide
execution of Predictive Model Markup
                                             parallel processing. Sybase IQ also offers   range of analytics workloads – allowing
Language (PMML) models through a
                                             an In-database analytics simulator, which    organizations to analyze hundreds of
certified plug-in from Zementis. This
                                             allows you to test a custom built UDF        terabytes, even petabytes of data in
allows you to automate the execution
                                             before deploying it into a production        speeds up to 100 times faster – you can
of analytic models defined using industry
                                             database.                                    see that the big data challenges introduced
standard language and that are created in
SAS, SPSS Clementine, and other popular                                                   at the beginning of this article – volume,
                                             As you can see in-database analytics is a    velocity, variety, costs and skills, are
predictive workbench products. By using
                                             key component to Sybase IQ’s success in      matched with the growing set features
industry standard languages it enables
                                             being an advanced analytics platform for     and capabilities offered by SAP Sybase IQ.
you to leverage your existing investments
                                             Big Data. Data volume, accuracy, and swift Now with accurate complete information
while providing better performance and
                                             processing time are all factors critical for across your enterprise, Big Data doesn’t
scalability.
                                             success but the balancing act between        seem like such a Big Problem it has turned
                                             these key components continues to pose       into a Big Advantage – with SAP Sybase
Within Sybase IQ, the row store SQL
                                             serious challenges for most organizations. IQ!
Anywhere engine, allows you to also
                                             With traditional analytics this data
create indexes of geospatial information
                                                                                            Source: Sybase




4
Gartner Reserch: Magic Quadrant for Data Warehouse
Database Management Systems
The data warehouse DBMS market              used as a data warehouse – rather, a data     data (SSED), excluding all data warehouse
is undergoing a transformation with         warehouse (solution/data architecture)        design-specific structures (such as indexes,
the introduction of “big data” and the      is deployed on a DBMS platform. A data        cubes, stars and summary tables). SSED
logical data warehouse demand for new       warehouse solution architecture can           is the actual row/byte count of data
techniques in practices and technology.     and often does, use many different data       extracted from all sources.
The integration of professional services    constructs and repositories. Importantly,     From 2012 onwards, defining the size of
with product offerings also increased in    the definition of this market is changing     a warehouse will become less important
importance in 2011.                         and a DBMS will become only part of the       and information asset access will become
                                            overall market definition as the logical      more important. Within SSED it is
Market Definition/Description               data warehouse (LDW) continues to             important to separate the actual data size
This document was revised on 05 March       grow in acceptance and deployment.            in a data warehouse from the database
2012. The document you are viewing                                                        total size. Gartner clients report that
is the corrected version. For more        A data warehouse is a database in which         many 100-terabyte warehouses often
information, see the Corrections page on  two or more disparate data sources can          hold less than 30 terabytes of actual data.
gartner.com.                              be brought together in an integrated,           Throughout 2012 and 2013, the size of a
                                          time-variant information management             warehouse will evolve toward a combined
The supplier side of the data warehouse   strategy. Its logical design includes the       metric, relative to the repositories under
database management system (DBMS)         flexibility to introduce additional disparate   direct management of the warehouse and
market consists of those vendors          data without significant modification           complemented by the volume of available
supplying DBMS products for the database of any existing entity design. A data            information accessed by the warehouse,
infrastructure of a data warehouse and    warehouse DBMS is now expected to               as well as its performance in doing so (see
the required operational management       coordinate virtualization strategies, as        Note 3).
controls.                                 well as distributed and/or processing
                                          approaches such as MapReduce, to                In addition, for the purposes of this
For the purposes of this Magic Quadrant   handle one aspect of big or extreme data        analysis, we treat all of a vendor’s
analysis, a DBMS is defined as a complete situations.                                     products as a set. If a vendor markets
software system that supports and                                                         more than one DBMS that can be used
manages a logical database or databases   A data warehouse can be of any size. The        as a data warehouse DBMS, we note
in storage. Data warehouse DBMSs are      sizing definitions of traditional warehouses    this fact in the section related to the
systems that, in addition to supporting   remain as:                                      specific vendor, but evaluate its products
the relational data model (extended to        •	 Small data warehouses are less than      together as a single entity. Further, a
support new structures and data types            5 TB.                                    DBMS product must be part of a vendor’s
such as materialized views, XML and                                                       product set for the majority of the
                                              •	 Midsize data warehouses are 5 TB
metadata-enabled access to content),                                                      calendar year in question. If a product
                                                 to 20 TB.
support data availability to independent                                                  or vendor is acquired mid-year, it will be
front-end application software and            •	 Large data warehouse are greater         labeled appropriately but placed separately
include mechanisms to isolate workload           than 20 TB                               on the Magic Quadrant until the following
requirements (see Note 2) and control                                                     year (see Figure 1).
various parameters of end-user access       Importantly, none of these categories
within a single instance of the data.       qualify a warehouse as a “big data”           There are many different delivery models,
                                            warehouse. Volume alone is not “Big           such as stand-alone DBMS software,
This market is specific to DBMSs used       data.” For the purpose of measuring the       certified configurations, data warehouse
as a platform for a data warehouse. It is   size of a data warehouse database, we         appliances (see Note 1) and cloud (public
important to note that a DBMS cannot be     define data as source-system-extracted        and private) offerings. These are also
                                                                                          evaluated together within the analysis of
                                                                                          each vendor.




                                                                                                                                  5
Figure 1. Magic Quadrant for Data Warehouse Database Management Systems                                   is either a visionary with cloud
                                                                                                          and data warehouse as a service,
                                                                                                          but does not execute against the
                       challengers            leaders
                                                                                                          rest of the market, or it is good at
                                                                                                          execution against two of the many
                                                                                                          use cases in the market with little
                                                             Teradata                                     vision for the remainder.
                                                       Oracle                                          	 The 1010data position is almost
                                                     IBM                                                  perpendicular to our combined
                                                   EMC/Greenplum                                          evaluation criteria. Therefore, we
  ability to execute




                                               Sybase, an SAP Company                                     have placed it with high execution
                           1010data
                                                                                                          against a sub-section of the market
                                                  Microsoft
                                                                                                          we evaluate. From a visionary
                                   ParAccel     Vertica                                                   perspective, 1010data is difficult
                            Kognitio
                                                                                                          to evaluate under current criteria.
                       SAND Technology
                                                                                                          Its approach in using a cloud-
                         Infobright                                                                       based and “as a service” DBMS/
                                                                                                          analytics solution is the primary
                            Actian                                                                        business model and technology
                                                                                                          approach. Cloud-based analytics as
                                                                                                          a service and the ability to deliver
                              Exasol
                                                                                                          under a managed on-premises
                       niche players          visionaries                                                 model, leaves 1010data short of
                                                                                                          the much broader vision desired
                                  completeness of vision                                                  by the greatest portion of the
                                                      As of February 2012
                                                                                                          data warehouse market, but in
                                                                                                          these few delivery segments of the
  Source: Gartner (February 2012)                                                                         market 1010data is a formidable
                                                                                                          performance competitor.
                                                                                                       •	 1010data is expected to add
Magic Quadrant                                              share large amounts of data without           probabilistic matching in 2012.
                                                            needing to manage it locally – for            The company has exhibited
Vendor Strengths and Cautions
                                                            example, large quantities of CPG              significantly more reduced load
1010data                                                                                                  times than some of its significant
                                                            data can be shared by multiple retail
1010data (www.1010data.com) was                                                                           big data competitors, as well as
                                                            companies.
established 11 years ago as a managed                                                                     orders of magnitude and faster
service data warehouse provider with an                   	 As a managed service solution
                                                                                                          performance in extremely large
integrated DBMS and business intelligence                   vendor, 1010data can complement
                                                                                                          datasets. 1010data products read
(BI) solution primarily for the financial                   the customer’s internal IT
                                                                                                          SQL, but also utilize their own,
sector and more recently, the retail/                       department with fast-to-market
                                                                                                          non-SQL language that performs
consumer packaged goods (CPG) sector.                       solutions for business units, so
                                                                                                          high-speed joins with unplanned
1010data can host its solution using                        reducing resource consumption
                                                                                                          data rationalization built into the
traditional software as a service (SaaS)                    within the IT department. More
                                                                                                          queries without the performance
model or support a managed solution                         importantly, the managed service
                                                                                                          disadvantages of using interim
at the customer’s site. 1010data has                        model enables 1010data to leverage
                                                                                                          return datasets.
approximately 200 customers.                                software solutions across multiple
                                                            customers. As new applications are         •	 Perhaps the most important
Strengths                                                   created, they become available to             point raised by those customers
                                                            all clients, increasing the availability      referenced is that 1010data is
   •	 Since 1010data offers a complete                                                                    utilized by both IT and the business
                                                            of these applications to businesses.
      SaaS solution, the customer’s                                                                       with fast response times on queries
                                                            With more than 200 customers,
      business unit and IT organization                                                                   running against hundreds of billions
                                                            1010data has reached a position to
      need little experience of data                                                                      of row tables (with a combined
                                                            break out of its former niche status.
      warehousing or BI. The SaaS model                                                                   number of rows throughout
                                                            The problem is that the company
      also allows multiple organizations to
6
databases exceeding a trillion rows       As the demand for hybrid analytics       Actian
     in the entire database in some            mixing structured data with content      Actian (www.actian.com) offers two
     instances). The company also              increases, 1010data will need to         products, the general-purpose Ingres
     serves as a data aggregator and data      introduce unstructured data analysis     DBMS and Vectorwise, a new offering
     marketplace providing datasets for        as well as operational technology        introduced in June 2010 and targeted at
     rapid enhancement and enrichment          or machine-generated data analysis.      analytic data warehouses. Open-source
     of analytics normally bound to            1010data’s competitors have greater      Ingres, one of the original RDBMS
     internal datasets only.                   financial resources and already are      engines, has a 30-year history and claims
   	 Our reference checks and                  in the process of building out this      more than 10,000 customers running
     discussions with Gartner clients          part of the data warehouse vision.       mission-critical applications, including data
     also show that 1010data is             •	 One of 1010data’s strengths              warehouses.
     price-competitive with non-SaaS           also acts as a caution. While the
     alternatives, especially by reducing      business prefers a solution that is a    Strengths
     the management overheads needed           complete, deployment-ready stack,           •	 The Actian database contains most
     to support a data warehouse               IT departments and purchasing                  of the features necessary for data
     environment. 1010data has                 offices do not. 1010data’s offering is         warehousing, such as partitioning,
     expanded from the financial sector        sold as a fully integrated DBMS and            compression, parallel querying
     (where it began) into a broader           BI solution, which limits potential            and multidimensional structures.
     market, including the retail sector.      customers to those wanting a                   Release 10 added bulk load, scalar
     1010data now claims more than             full solution (primarily because               subqueries, long identifiers and
     200 customers and its customer            of 1010data’s pricing model).                  a geospatial offering that was
     references support our belief that        1010data’s product is a compliant,             community driven with hundreds
     it is one of the stronger small           relational DBMS (RDBMS) that                   of committers contributing code.
     data warehouse DBMS vendors.              customers can use as a stand-alone             The performance of Vectorwise,
     In addition, the company has a            system if desired – but fees are               especially in analytic applications,
     small number of customers that            charged as if the entire solution is           was cited by customers interviewed
     install its system on-premises as         managed. Customers are advised to              by Gartner. With the emergence
     a managed solution, with several          check the total cost of ownership              of new server platforms with
     using 1010data as an enterprise           in such cases, as it may not be                storage-class memory (of 1 TB and
     data warehouse solution vendor.           advantageous to use 1010data in                more), Vectorwise will prove a
     Therefore, from an execution              this way.                                      valuable asset for data warehousing
     standpoint, 1010data matches           •	 As a solution vendor, 1010data                 and analytics as more of the data
     performance, pricing and delivery         has a different competitive                    warehouse moves to memory.
     model for two specific needs in           model from vendors of pure-play             •	 Actian has aggressively pursued
     the market quite well and it is           DBMS offerings. In addition to                 partners, including independent
     expanding both its scope of delivery      competing in the data warehouse                software vendors (ISVs) in the BI
     and its vertical customer base.           DBMS market, it competes with                  market, the primary driver of new
                                               system integration vendors that                installations in data warehousing.
Cautions                                       offer outsourced solutions, such               Both new and existing customers
  •	 The market continues to resist            as Cognizant and HP (via EDS).                 are looking for an open-source
     fully-managed data warehouse              Additionally, IBM, Oracle and other            BI stack with partners such as
     services in many verticals and            large vendors with professional                Jaspersoft and commercial BI
     horizontal use cases. 1010data is         service organizations compete with             vendors such as MicroStrategy
     susceptible to resistance from IT         1010data in two markets, data                  have also engaged with Actian.
     departments requiring all its data        warehouse DBMSs and services. It               Ingres and Vectorwise are gaining
     warehouses to be located in-house,        remains to be seen if this is a bias           attention from vertical application
     along with in-house governance            to be overcome or if the cloud                 vendors, system integrators and
     of the organization’s data assets.        and on-premises mix will ultimately            resellers. Vectorwise uses some
     The IT market is not fickle and           exclude a vendor like 1010data.                Ingres software atop a column store
     persists in its use of better name-       However, based on its extremely                from the MonetDB project and uses
     branded vendors and not simply            positive customer references, it               hardware assists, turning columns
     because they are name-branded.            is very unlikely 1010data will be              into vectors and processing them
                                               excluded from such a mix.                      in x86 chip registers to leverage

                                                                                                                                  7
instruction parallelism and on-chip        •	 Actian offers professional services     Strengths
       caching. Vectorwise has delivered             in data warehousing and has a go-          •	 Greenplum’s understanding and
       several top non-clustered TPC-H               to-market strategy with a growing             vision of the data warehouse
       benchmark results at 1 TB and                 stable of partners – it claims half           market was ahead of the market as
       below. The company was renamed                of its 2011 Vectorwise sales have             it was one of the first to work with
       in late 2011 and introduced another           come though channels. However,                MapReduce, manage external files
       new product offering, the Cloud               it lacks data models and must                 from within the DBMS and optimize
       Action Platform, to support the               continue to add marketing and sales           for very large database sizes. As
       delivery of “Action Apps” that                expertise for data warehousing.               big data is now important in the
       will act on the analytic capabilities         Additionally, Actian has strength             market and the LDW is emerging as
       Actian supports.                              in open-source, but the overall               a necessary functionality to support
    •	 Previous reference checks have                adoption of open-source for data              today’s mix of volume, velocity,
       shown Ingres customers to be very             warehousing remains weak. While               variety and complexity, Greenplum
       loyal. Most have online transaction           Actian has professional services, it          has a base to support this that was
       processing (OLTP) applications,               tends to lack some of the tools and           launched several years ago, which
       but Ingres has also been used                 methodology support that other                translates into the high ability to
       for smaller data warehouses                   organizations have readily available.         execute.
       (historically up to about 2 TB, the        •	 Actian’s new brand and name, as               Greenplum announced the first
       company is targeting warehouses               well as its portfolio expansions, can         unified analytics appliance addressing
       smaller than 10 TB). Among open-              help overcome Ingres’s reputation             big data (a modular solution for
       source DBMS, only Oracle’s MySQL              as an older product that has not              structured and unstructured data),
       compares with proven maturity                 regained much market traction.                in May 2011 that was released
       for mission-critical applications,            Importantly, Actian has taken a bold          in September 2011. The EMC
       including data warehousing.                   stance in attempting to re-establish          Greenplum Data Computing
       Vectorwise has begun to gain new              itself with a new vision and new              Appliance (DCA) uses the
       customers and software partners,              plans for execution. Initial response         Greenplum Database, Greenplum
       targeting another set of use cases.           to Vectorwise is significant with the         HD (Hadoop), and Greenplum
       Now in its version 2.0, it has added          addition of more than 20 customers            Data Integration Accelerator (DIA)
       Windows as a platform and has a               in its first year offering and users          modules that can be configured
       clear road map for several future             should consider Actian’s Vectorwise           within one single appliance cluster.
       releases.                                     to be a new and innovative                    In addition, Greenplum has Chorus,
                                                     solution in that respect. However,            its analytics productivity software,
Cautions                                             market perception is difficult to             leveraging VMware’s technology, to
                                                     change. Both offerings have gained            support automated, self-service data
  •	 Although Vectorwise enhances
                                                     new customers and third-party                 services and collaborative analytics.
     Actian’s ability to support analytic
                                                     relationships, but to become a                In a recent announcement, EMC
     data marts, the company must
                                                     serious competitor in this market             announced the first Hadoop NAS
     continue to address enhanced data
                                                     Actian must continue to show                  attached HDFS system – HDFS
     warehouse functionality, storage
                                                     increased growth in both revenue              running native on EMC Isilon
     management and mixed workload
                                                     and numbers of new customers at               connected to the Greenplum HD
     management if it is to compete
                                                     a higher rate than it has thus far.           or Greenplum Data Computing
     with larger, equally mature vendors
                                                     Effective marketing execution is a            Appliance (DCA). Finally, through
     and meet the needs of the broader
                                                     must-have for Actian to compete.              the external file mechanisms and
     data warehouse DBMS market.
     Vectorwise needs to support more                                                              user defined functions (UDF),
     analytic SQL constructs than it does      EMC/Greenplum                                       Greenplum has started along the
     now and add stored procedures             Greenplum (www.greenplum.com) is part               path to support LDW. Greenplum
     and user-defined functions and            of the Data Products division of EMC                even supports an iOS, Linux and
     data types to move closer to              with a massively parallel processing (MPP)          Windows single-user development
     competitors. Its new product and          data warehouse DBMS running on Linux                system downloadable as free (not
     restructuring around Action Apps          and Unix. It can be sold as an appliance or         open-source) software.
     can be synergistic – but could also       as a stand-alone DBMS and has more than          •	 As Greenplum has settled into
     prove distracting.                        400 customers worldwide.                            the EMC organization, we have


8
seen an increase in hiring directly         presence to compete with all the        Exasol
      related to development. This,               incumbent, large DBMS vendors.          Exasol (www.exasol.com) is a small DBMS
      coupled with the EMC development            Importantly, EMC’s customer base        vendor in Nuremberg, Germany. Exasol
      organization has led Greenplum              is primarily within the IT unit of      has been in business since 2000 with the
      to offer its DCA supporting big             the organization. Data warehousing      first in-memory column-store DBMS,
      data for both structured and                is the technical infrastructure for     EXASolution, available since 2004 and
      unstructured data and intergraded           an intensely business-oriented          primarily used as a data mart for analytic
      MapReduce processing. The DCA               use-case. EMC will need to learn        applications.
      is now assembled by EMC and sold            from its Greenplum acquired
      by its sales force. In an interesting       knowledgebase, specifically how to      Strengths
      manufacturing cost management               solution sell a data warehouse and         •	 Exasol offers an in-memory column-
      model, EMC is assembling its                analytics solution.                           store DBMS for data warehousing.
      appliances in different countries        •	 Interestingly, this year our customer         As we have stated, this technology
      around the world, affording EMC             references have raised several                is one of the critical capabilities of
      Greenplum a tax advantage in many           issues around support. In these               the future for the data warehouse
      countries where others (such as             cases it was not related to the               DBMS market. Exasol runs in a
      Oracle and Teradata) are subject            attention to rapid support and                clustered environment offering
      to stiff import duties. This positions      fixes (with all customers stating             scalability across multiple servers.
      the company for easier entry                fixes were available in an expected,          Not only does this allow for high-
      into global markets. Due to the             timely manner), but more with                 availability in the case of a server
      acquisition, Greenplum has been             the bugs in the first place. We               failure using EXACluster OS, but
      able to work more closely with              would classify these as “growing              also scaling for larger memory sizes.
      VMware, for example rearchitecting          pains” especially for a small                 EXASolution maintains redundant
      the Chorus private cloud offering.          organization (as Greenplum was                copies of the data in memory to
   •	 Our customer references support             pre-acquisition) being integrated             reduce the downtime associated
      the claims of high performance              into a large organization such as             with server failures.
      as well as advantageous price/              EMC. We should also note that in              Exasol also includes the use of disk
      performance ratios. These                   our inquiries with Gartner clients,           for persistence and overflow (if all
      references also support the                 we have seen this issue diminish,             the data does not fit in memory).
      Greenplum claim of scalability to           coupled with consistently high                However, when data is loaded into
      very large database sizes. Reported         marks for personalized customer               Exasol, it is loaded into memory
      sizes range from 10 terabytes to            support.                                      first and then written to the disk,
      more than 500 terabytes. When            •	 As Greenplum leverages EMC                    allowing for the applications to
      this combination of performance             more, it will find itself competing           begin before the slower activity
      and scalability are joined to an            at a higher level with the mature,            of disk input/output (I/O) is
      appliance, the potential of EMC/            incumbent vendors. The major                  completed. This separation of the
      Greenplum to compete in the data            vendors (such as IBM, Oracle, SAP             data access and data persistence
      warehouse market is increased.              and Teradata), have a much larger             model is a visionary change for the
                                                  customer base allowing them, as               market. Additionally, as a column-
Cautions                                          the incumbent, a stronger position.           store, Exasol has excellent data
  •	 Although acquired by EMC 18                  EMC/Greenplum must continue                   compression (reported to be on
     months ago and despite doubling              to demonstrate differentiation as             average, four times faster), thus
     the install-base, Greenplum’s                it addresses the data warehouse               reducing the amount of memory
     market position is sixth or seventh          market and big data is one specific           necessary. EXASolution is sold by
     worldwide. To really increase                area, as is cloud. The company must           the amount of memory used for the
     velocity and gain market share,              continue to support customers                 data.
     Greenplum must continue to                   accustomed to the type of service          •	 Another advantage of Exasol, as
     develop the EMC sales force so               provided by a small company                   with other in-memory DBMSs, is
     that it has the necessary skills             with focused, customer-specific               the high speed of the DBMS. In
     in the DBMS software market.                 professional services solutions,              published benchmarks, Exasol has
     Greenplum must also continue                 issue-focused support and leveraging          attained data warehouse transaction
     to leverage the EMC worldwide                key customer inputs for product               speeds up to 20 times the closest
                                                  enhancements.

                                                                                                                                  9
competitor. Server memory                  Exasol lacked a marketing vision                 vendors such as Quest are less
      is expensive, but these same               to grow beyond the borders of its                likely to support the DBMS,
      benchmarks demonstrated costs              European base. The company began                 requiring Exasol to create their own
      of approximately one-third of the          an expansion plan in 2011 and                    management software.
      standard DBMS. Our reference               will begin to grow offices in other
      checks also validate the claims of         locations, including North America.
                                                                                            IBM
      cost reduction and speed. Another       •	 Another issue is the increasing            IBM (www.ibm.com) offers stand-
      strength of the in-memory nature           competition, both in column-store          alone DBMS solutions as well as data
      of Exasol is removing the necessity        and in-memory. Exasol has a clear          warehouse appliances, currently marketed
      of optimization and calculation            advantage being the first with an          as the IBM Smart Analytics System family
      structures within the database.            in-memory column-store DBMS.               (ISAS) and the Netezza brand. IBM’s
   	 There is no need to build                   Now, most of the DBMS vendors              data warehouse software, InfoSphere
      summaries, aggregates and cubes            offer some form of column-store            Warehouse, is available on Unix, Linux,
      for use in business intelligence           capabilities. Further, when Exasol         Windows and z/OS. IBM has also
      and analytics. This reduces the            began, there were only a handful of        continued research and development and
      overhead in the DBMS by as much            in-memory DBMS, mostly used for            market execution for the Netezza brand
      as 10 times, as well as reducing           streaming data applications. There         and product line following its acquisition.
      the database administrator (DBA)           are now many in-memory DBMSs               IBM has thousands of database customers
      resources used to maintain such            available in both the column and           worldwide and more than 500 appliance
      structures. In addition, this also         row-store variety. Finally, SAP has        customers (Netezza and ISAS combined).
      leads to very fast load times,             released its SAP HANA appliance
      as there are no complicated                with an in-memory column-store             Strengths
      structures to build during loading.        DBMS for an analytics data mart
                                                                                               •	 The breadth of IBM technology
   •	 Customer references clearly                and now available under the SAP
                                                                                                  offerings is complementary to
      espouse the abilities of                   NetWeaver Business Warehouse.
                                                                                                  and part of its solution delivery
      EXASolution for both pure                  As with many technologies,
                                                                                                  capability. InfoSphere Warehouse,
      performance and cost/performance.          being first is not sufficient unless
                                                                                                  a data warehouse offering based
      The references (although few in            capitalized in growth of market
                                                                                                  on IBM DB2, is a software-only
      number) also state that customer           share. Exasol has missed the
                                                                                                  solution. IBM’s data warehouse
      support is excellent. Finally,             window of opportunity of being
                                                                                                  appliance solution, the IBM
      references corroborate the results         first and now faces increased
                                                                                                  Smart Analytics System (ISAS) is
      of the benchmarks mentioned                competition.
                                                                                                  a combined server and storage
      here, with better than 20 times         •	 Customer references report that                  hardware solution (using the IBM
      performance at half to a third             there is one major issue with the                Power Systems server with AIX,
      of the cost. They also support             use of EXASolution – the lack of                 the System x server with Linux or
      the claims of 4 times (or more)            interfaces to common BI tools.                   Windows and the IBM InfoSphere
      compression.                               Exasol offers the standard ODBC                  Warehouse and a robust System
                                                 and JDBC interfaces, but this can                z ISAS data warehouse solution),
Cautions                                         be a performance drawback with                   complete with service and support.
                                                 tools such as BusinessObjects,
  •	 The primary challenge Exasol faces                                                           IBM’s introduction of InfoSphere
                                                 Cognos and SAS. As Exasol has a
     is the small size of the company and                                                         BigInsights includes offerings to aid
                                                 small installed base, it is difficult to
     previous lack of expansion beyond                                                            the design, installation, integration
                                                 engage the tools vendors to assist
     Germany. Exasol was primarily                                                                and monitoring of the use of
                                                 in creating native interfaces to the
     engaged in product development                                                               Hadoop technologies within an
                                                 DBMS. We do expect to see this
     for its first five years of operations                                                       IBM-supported environment. In
                                                 remedied over the next few years
     and with changes in management                                                               IBM’s case, it is important to note
                                                 as the size of the installed base
     two years ago has now obtained                                                               that it has embraced the vision
                                                 grows. Similarly, there is a reported
     the vast majority of its 30 or more                                                          for the LDW – which Gartner
                                                 lack of software to manage the
     customer base in the past two                                                                describes as the emerging new best
                                                 Exasol environment (EXASolution).
     years. These customers are mostly                                                            practices in analytics management.
                                                 Again, with a small installed base,
     located in Germany, with several in                                                          By tying together relational data,
                                                 third-party management software
     Italy and Japan. Until very recently,                                                        data streams and Hadoop files,


10
IBM’s stack builds confidence among         IBM specifically assigns technical         own methodology and highlights
   managers of existing warehouse              account managers to support                that the traditional enterprise data
   implementations that the product is         accounts). Additionally, IBM’s focus       warehouse [EDW] is vital to all data
   evolving as new demands for these           on prospect qualification resulted in      warehouse strategies including as a
   two components of the logical data          a higher growth in 2011 vs. 2009 to        base component for the LDW.
   warehouse emerge.                           2010 for all of its products.              This was IBM’s first incarnation of
	 Additionally, for Smart                   •	 The overall effect is that referenced      the LDW approach. The market
   Consolidation – rather than                 customers are confident regarding          is acknowledging that the EDW
   developing tooling in isolation, IBM        release dates and the road map.            does not have to be the center of
   focused on tooling that existed in          Customers list concurrency,                the strategy but will be significant.
   its Information Integration portfolio       scalability, performance optimization      However, the justification for
   (InfoSphere BluePrint Director).            and support as positives and were          the LDW and evolving existing
   This resulted in improvements in            the most often repeated phrases            warehouses or replacing them
   the area of integration, including but      in the reference survey in 2011.           will be difficult at first because
   not limited to the common Data              References elaborated by indicating        it appears to supporters of
   Warehouse Packs and Models now              that partitioning, compression and         traditional data warehouses to
   supported on DB2 and Netezza                reduced administrative hours all           be a radical departure from their
   platforms alike.                            contribute to their experience to          beloved traditional data warehouse
•	 IBM combines product sales with             support optimized performance.             practices. Gartner’s own research
   solution services. This market           	 At the same time, some references           indicates that the LDW approach is
   demands a widely varied level               reported that optimization of              quickly emerging as the newest data
   of sophistication and knowledge             queries should be targeted rather          warehouse best practice. Gartner
   depending on each client                    than being forced to optimize every        anticipates the LDW will become
   organization’s maturity in analytics        single query because the system is         a best practices approach during
   and information management. As              able to engage a solid query plan for      2013-2015. With market leadership
   noted in the overview, the data             execution. This evaluation considers       there is risk commensurate with the
   warehouse market in 2011 has                the LDW concept to be innovative,          anticipated rewards. IBM will need
   multiple visions for the future.            but has yet to see a wider embrace         to continue their careful education
   IBM has embraced the logical                in the market. IBM’s early adoption        message regarding their leadership
   data warehouse (via “Smart                  of the LDW concept in both its             approach in LDW practices. When
   Consolidation”) approach while              messaging and its product road             engaging in an LDW approach
   continuing to advance its technology        map has established this vendor as         with IBM, clients should insure
   solutions and implementation                an early resource for the market.          they completely understand IBM’s
   practices supporting traditional data       However, the majority of the               positioning for implementing this
   warehousing architectures.                  market for data warehousing will           solution.
   Professional services available             remain significantly focused on         •	 Gartner inquiries report indicate
   from IBM range from expert                  traditional solutions for a minimum        that IBM data warehouse solutions
   education through turnkey                   of the next three years.                   are also marketed and delivered in
   solutions to managed services for                                                      isolation from each other. There are
   data warehousing. Importantly,         Cautions                                        strategic reasons to continue such
   where IBM leverages its services                                                       an approach with any acquisition,
                                            •	 IBM has embraced the logical data
   organization most, is in feeding                                                       but Netezza products tend to have
                                               warehouse vision as the likely
   field experiences into the overall                                                     their own niche in customers’ minds
                                               successor to current best practices
   data warehouse vision. In 2010,                                                        that is viewed as being separate and
                                               in traditional data warehousing. The
   clients reported that IBM’s support                                                    distinct from IBM (but Netezza’s
                                               market has not yet determined if
   appears disconnected from its                                                          growth was more than 30% in 2011,
                                               it is ready to adopt this approach
   product strategy – this improved in                                                    which is faster than its previous
                                               as the new vision for the data
   2011 with an even larger reference                                                     growth rate as an independent
                                               warehouse and abandon 20 years
   base reporting. This does not mean                                                     company).
                                               of traditional best practices.
   the issue has been resolved, but it         IBM’s professional services have        	 As a result, IBM customers often
   appears that IBM’s focus on solution        experience in delivering various           engage only part of the organization
   services is paying off (for example,        aspects of the LDW under its               for solutions and at least in the


                                                                                                                        11
customer’s minds, eliminate the          compressed DBMS. The company                    	 Infobright also released an option
      others. This creates both marketing      provides both an open-source version               for the Enterprise Edition called the
      and sales process challenges. This       (Infobright Community Edition [ICE])               Distributed Load Processor (DLP)
      is not an issue with shortlisted         and a commercial version (Infobright               which allows for the parallel loading
      solutions (IBM should recommend          Enterprise Edition [IEE]). Infobright has          of data into the system at very high
      one solution or another), but does       approximately 200 customers worldwide.             speeds. Infobright has also added
      carry over into the solution delivery                                                       connectivity to Hadoop MapReduce
      team and IBM is missing some             Strengths                                          for the processing of “Big data.”
      opportunities for the different parts       •	 Infobright remains one of the only           This is extremely important to
      of the sales organization to leverage          column-store DBMS in the open-               the machine-generated data world
      each other. IBM has implemented                source software environment.                 as much of this data is stored in
      organizational changes intended to             Its revenue is generated from                Hadoop or other such file systems
      address these issues.                          the Enterprise Edition (using a              and needs to be extracted into a
   	 Netezza and IBM personnel do                    commercial license, rather than a            DBMS for processing.
      interact and coordinate with                   General Public License [GPL]) with        •	 Our customer references are clear
      each other behind the scenes.                  a subscription support model based           on several points. Infobright is
      A marketing solution would                     on the amount of SSED stored in              extremely fast compared to other
      simply begin branding software                 the system. As we stated in 2011,            systems, including MySQL. Reports
      and hardware combinations for                  Infobright decided in mid-2010 to            of up to an average 500% increase
      limited purposes. However, IBM                 focus on operational technology              in performance over MySQL
      will choose the more difficult (and            data (which it calls machine-                deployments have been reported.
      more appropriate) solution of                  generated data). This encompasses            We believe this is not only from
      creating an educational sales and              data from sources such as smart              the column-store design, but also
      implementation process which                   meter data (in the utilities space),         the Knowledge Grid. References
      will demonstrate how software                  customer data records (in the telco          suggest that Infobright is replacing
      and hardware capabilities can be               space) and clickstream data from             an existing MySQL environment
      leveraged effectively to support               Internet interactions.                       with great gains in stability,
      each use case.                              	 This focus has helped Infobright              compression and performance.
   •	 IBM customers report (via inquiry              during 2011 where its customer               Some cases report a year or more
      and reference survey results)                  base has grown to more than 200              without an outage.
      a scattering of intermittent                   direct and OEM channel customers.         	 Finally, many references state that
      and irregular issues with                      Not only has this focus increased            simplicity is a factor in their choice
      product performance or their                   customers, but has also attracted            to use Infobright. We also believe
      implementation experience. Some                a number of additional OEMs                  this will interest OEMs that want to
      of these are possibly attributed to            (now accounting for approximately            build-in Infobright to their existing
      the implementation process and                 40% of customers). This, along               systems for resale. The simplicity
      not the products. However, these               with partnerships with Pentaho,              of management, scalability and
      same customers report that IBM                 Jaspersoft, Talend and others, will          compression all interest the OEM
      support addresses these issues with            help the company grow substantially          looking for a DBMS to embed that
      efficiency. Nonetheless, as with               faster than direct sales only.               requires little support on their part.
      any IT products, an assumption              •	 Infobright has several unique                The focus on machine-generated
      that appliances or certified                   technologies in the DBMS. In                 data has been important to
      configurations alleviate all issues is         addition to the column-store file            Infobright, but we believe that the
      incorrect. Most issues are irregular           system for MySQL, the Knowledge              future will greatly depend on the
      in nature and IBM support is                   Grid in-memory metadata store                company’s ability to leverage these
      intimately involved in the resolution          is a major differentiator for                OEM partners.
      process.                                       Infobright, as this product analyzes
                                                     queries to minimize the number         Cautions
Infobright                                           of “data packs” that have to be          •	 One of the biggest challenges for
Infobright (www.infobright.com) has                  decompressed to give a result (data         a small vendor is to focus on what
offices in Canada, Europe and the                    packs are the compressed domains/           they do well. Infobright has done
U.S. and offers a combination of a                   regions of data in Infobright’s             this with machine-generated data.
column-vectored DBMS and a fully                     offering).

12
However, as a small, relatively              MySQL. To date, Oracle has not             started to produce results, with
   young vendor, Infobright must                done anything other than enhance           several new customers. Kognitio
   continue to differentiate its                the product. However, in the future        has also added several hosting
   offerings and open-source model              when the contract is done with EU,         partners in the U.S. and the U.K.
   from mature column-store DBMSs.              we cannot guarantee that Oracle            offering managed services on WX2.
   Sometimes, these two statements              will not change the agreements,            Its sales model as dbSaaS makes up
   are contradictory not least because          especially those with OEMs. This           almost half of its revenue and has
   the focus on machine-generated               is an issue customers of Infobright        supported much of the company’s
   data cannot be an excuse for                 should monitor in the future.              growth this year.
   ignoring its existing customers                                                      •	 Kognitio continues to invest in
   addressing other data management                                                        in-memory capabilities. Gartner
                                           Kognitio
   use cases, reported in several                                                          considers that in-memory DBMSs
                                           Kognitio (www.kognitio.com) started by
   customer references as an issue. An                                                     can play a major role in enterprises
                                           offering data warehouse appliances and
   example is workload management                                                          information infrastructure and as
                                           warehousing as a hosted service. Today,
   software, where the managed                                                             such Kognitio’s technology has
                                           it has a mixture of less than 50 customers
   workloads are basically for machine-                                                    an opportunity to meet customer
                                           using its DBMS (WX2) separately as an
   generated data and may lack the                                                         demand, given the maturity of its
                                           appliance, a data warehouse DBMS engine,
   robustness needed for management                                                        offering, compared to other more
                                           or data warehousing as a managed service
   of overall workload.                                                                    recent offerings. Kognitio’s DBMS,
                                           (hosted on hardware located at Kognitio’s
•	 There are other issues raised by        sites or those of its partners).                WX2 version 7, already includes
   our reference checks. As with most                                                      in-memory analytics, and customer
   small startup vendors, stability from   Strengths                                       references continue to report
   one release to another can suffer.                                                      that the speed of query and load
                                              •	 Kognitio pioneered the data
   Customer references reveal that                                                         performance is excellent. In 2011,
                                                 warehousing database as a service
   there have been issues with new                                                         Kognitio added Pablo in-memory
                                                 (dbSaaS) model, where a data
   releases, but they are quick to point                                                   online analytical processing (OLAP)
                                                 warehouse DBMS is delivered
   out that the problems are quickly                                                       capabilities to further strengthen its
                                                 as a managed service from the
   resolved. The lack of management                                                        analytical capabilities The DBMS is
                                                 DBMS vendor. Clients buy data
   software (also an issue for smaller                                                     already an in-memory DBMS, with
                                                 warehousing services from Kognitio,
   vendors) was raised. Third-party                                                        hot data held in-memory and cold
                                                 while Kognitio hosts the database.
   software vendors are not quick                                                          data on disk, managed automatically
                                                 Data warehousing dbSaaS permits
   to pick up new, young software                                                          by the DBMS.
                                                 clients to expand their warehouses
   companies, as the potential market                                                   •	 Those customers referenced
                                                 incrementally and clients note
   is small, so this puts more pressure                                                    reported significant concurrency
                                                 that this model provides for low
   on Infobright to produce its own                                                        capabilities, as well as excellent
                                                 upfront costs with virtually no
   management software.                                                                    support and product management.
                                                 capital expenditure required to
•	 Finally, Infobright is open-source            get started. This is a growing            Kognitio is gaining visibility thanks
   and makes use of portions of                  segment of the data warehouse             to the current market interest in
   MySQL, under a Commercial OEM                 DBMS market. Kognitio also works          in-memory technologies. Kognitio’s
   License with Oracle. We always                with deployment partners such             customers report that deployment
   question the open-source model                as Capgemini (and contributes             of large-scale data warehouse
   for revenue generation. First,                to Capgemini’s Immediate cloud            efforts takes as little as 10 weeks
   Infobright has a community version            computing offering).                      using this model. References also
   with less functionality than the                                                        report predictable, linear scaling of
                                              	 Additionally, in line with existing
   Enterprise Edition. This has proven                                                     performance and under the “as a
                                                 market demands, Kognitio has
   useful as a trial system to attract                                                     service” model, customers report
                                                 an appliance to install on-site for
   new customers, but some may opt                                                         scale up and scale down needs as
                                                 customers requiring their own
   for the ICE version in lieu of the                                                      part of a solid account management
                                                 infrastructures. Kognitio opened
   Enterprise Edition.                                                                     approach. Finally and possibly most
                                                 offices in the U.S. three years ago
	 The other issue is specifically the                                                      importantly, references indicate that
                                                 in addition to its U.K. headquarters
   use of MySQL, as it is owned by                                                         new queries and new variations on
                                                 and has continued to expand its
   Oracle. This implies risks remain                                                       existing analytics can be deployed
                                                 presence in the U.S. by hiring
   due to the uncertain future of                                                          rapidly.
                                                 additional resources. This has

                                                                                                                          13
Cautions                                         such as those of IBM (Cognos)             can also leverage SharePoint and
 •	 Kognitio has a very substantial               and SAP (BusinessObjects), is             PowerPivot and the ability to
    opportunity in the small or midsize           difficult to manage. This problem         include an unstructured information
    business data warehouse and                   is compounded by Kognitio’s               type in analytics is the result of
    BI market thanks to its dbSaaS                small market penetration and the          its technology blend and this is a
    model. However, over the past                 resulting scarcity of tool expertise      strength that should definitely not
    year, managed services offerings              in the market. References also            be ignored.
    from IBM and HP/Vertica have                  report the absence of any form of      •	 References report that Microsoft
    experienced growing acceptance                developers’ forum or marketplace,         exhibits one of the best value
    and penetration in the market.                scarcity of skills in the market and      propositions on the market with
    These offerings are not direct                an extremely lean global presence         a low cost and a highly favorable
    competitors to Kognitio’s solution,           makes commitment to the product           price/performance ratio. Skills are
    but the customer base views them              and consistent delivery difficult.        widely available in the marketplace
    as an equal alternative from more                                                       to operate a Microsoft data
    established vendors.                     Microsoft                                      warehouse and there is an easy
 	 Kognitio has not yet addressed            Microsoft (www.microsoft.com) continues        learning curve to acquire those
    some of the very large volume            to market its SQL Server 2008 DBMS             same skills, as needed. As an added
    or variety of data support issues        (Release 2) Business Data Warehouse            bonus, customers report that the
    – more specifically support for          and Fast Track Data Warehouse for data         integration and continuity of a
    content and complexity aspects of        warehousing customers not requiring an         complete Microsoft data warehouse
    extreme information. However,            MPP DBMS. Microsoft released its own           and business intelligence stack is
    Kognitio’s in-memory analytical          MPP data warehouse appliance, the SQL          highly advantageous to time-to-value
    capabilities can be of value in low      Server 2008 R2 Parallel Data Warehouse         in delivery. Noticeably absent are
    latency, high volume analytics.          (Microsoft) (PDW), in November 2010.           any fears regarding vendor lock-in.
    The market shifted dramatically          Strengths                                      According to our reference checks
    during 2011 toward a new position.                                                      and discussions with our clients,
                                                •	 Microsoft spent 2011 revitalizing
    Kognitio did not stand still, but                                                       worldwide support from Microsoft
                                                   its vision for the data warehouse
    market demand regarding new                                                             is extensive, encompassing partners,
                                                   market. Additionally, it announced
    functionality expanded more rapidly                                                     value-added re-sellers, vendors of
                                                   two Apache/Hadoop connectors
    than Kognitio’s product feature                                                         third-party software and tools and
                                                   for SQL Server, SMP and Parallel
    sets. This appears to only be a                                                         widely available SQL Server skills.
                                                   Data Warehouse (PDW) in
    temporary condition while Kognitio             support of the market’s big data      •	 Microsoft references indicate a
    addresses these new expectations.              issues. Many would be surprised          dominant presence in midsize data
 •	 While Kognitio continues to grow               to learn that Microsoft already          warehouses —especially those
    its installed base (with an additional         provided combined structured             end-user organizations reporting
    seven clients in 2011) the company             and unstructured analysis in SQL         that their companies and their data
    remains a small vendor with fewer              Server 2008/R2. A third quarter          management needs are growing.
    than 50 customers worldwide.                   appliance update included support        According to customer references,
    This makes it increasingly difficult           and enhancements for integration         Microsoft assures its customers of
    to sell to organizations that have             with SAP/Business Objects,               a solid data warehouse platform
    incumbent vendors, and to compete              MicroStrategy and Informatica.           including features and functions
    with some of the lower-priced                                                           that run the gamut of traditional
                                                	 In addition, Microsoft offers the
    appliance offerings. Additionally,                                                      warehouse functionality.
                                                   SQL Server Fast Track Data
    as a data warehouse outsourcing                Warehouse, which includes             	 For connectivity in a multi-
    solution, organizations should be              validated reference architectures        vendor environment Microsoft
    aware that they are still responsible          for building a balanced data             offers a SAP/BW, Teradata and
    for contracting and auditing data              warehouse infrastructure. This           Oracle connector. The DBMS
    security procedures.                           road map contributes significantly       supports compression and
 •	 Clients report interoperability                to the company’s vision for the          backup compression, partitioned
    with third-party popular BI tools,             market and its customers. Microsoft      table parallelism, policy-based




14
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Sybase IQ ve Big Data

  • 1. Sybase IQ Issue 1 Introduction 2012 “Big Data” is the new hot topic for IT managers, and is causing quite a panic amongst some organizations; but, there is no need to panic, Big Data can be looked upon as Big Opportunity. IN THIS ISSUE With the data explosion companies now have access to more information than ever before – if the data can be exploited properly it can lead to a big competitive advantage. Introduction.........................1 With companies acquiring massive amounts of data in different forms from different sources, SAP Sybase IQ - Turning ranging from traditional channels with structured formats to social media channels with Big Data into a Big unstructured formats, it has changed the focus of analytics in the “real-world”. Throughout organizations there are changes in the way data is being analyzed – in marketing, the focus has Advantage............................. 2 shifted to digital channels – click streams and social media – to understand buying patterns, and Gartner Research: target marketing activities for maximum impact. In sales, the focus is on what we call “deal Magic Quadrant for Data DNA”, to correlate emails, meeting notes and chatter to assess the probability that a sales Warehouse Database deal will close. On the financial side, simulation is being used to predict margins and portfolio values; while on the operational side, machine data via sensors, and other kinds of digital data are Management Systems......... 5 being analyzed to track down operational inefficiencies – it’s no wonder companies are having About Sybase..................... 29 information overload and are at a loss as to how to manage the information let alone how to use that information intelligently. The key to Big Data is the ability to access and connect all the data no matter what type or where it came from, in order to achieve this you have to break the information silos that trap data – turning massive amounts of data into actionable insight while providing complete access to decision makers – creating an environment that offers “intelligence for everyone”. Featuring research from
  • 2. SAP Sybase IQ – Advanced volume, variety and velocity of today’s Massive Scalability Analytics Platform for massive data needs and demands in a cost effective and attainable manner. With a state of the art query processor Big Data Sybase IQ thrives on heavy ad hoc query Sybase IQ is based on a three layer usages by large numbers of concurrent SAP Sybase IQ is an analytic DBMS architecture. A strong data management users – it’s designed to handle it. Built designed specifically for advanced layer is the foundation with a highly on PlexQ™ technology framework that analytics, data warehousing, and business compressed column store, and shared delivers a shared-everything massively intelligence environments. Able to work everything distributed MPP elastic cluster parallel processing (MPP) architecture with massive volumes of structured and that supports a variety of workloads and based on a columnar data store, it unstructured data it is ideally suited to Big active user community. The application delivers new levels of performance. Data. services layer sits above that to provide Unlike shared nothing solutions, a PlexQ a variety of drivers, APIs, web services, grid dynamically manages analytics Sybase IQ is built on an open, flexible and federation capabilities to empower workloads across an easily expandable column-store technology, unlike developers. And wrapped around these grid of computing resources dedicated to traditional relational databases, that store two technology layers, is a rich ecosystem different groups and processes, making data by row, slowly working through of BI tools, partner libraries, packaged it simpler and more cost-effective to each row of entire tables, clogging I/O applications, and data integration tools support growing volumes of data and channels, memory, and disk, Sybase IQ to give you an end to end solutions. (See rapidly growing user communities. uses a strategy called “vertical portioning” Figure 1) that stores data by column, reading only the columns of data used by the query. With PlexQ grid technology, enterprise Using columns, not rows, delivers a 10 to Centralized Access to All IT departments can more easily overcome 100 times performance boost compared Your Enterprise Data the scalability limitations of traditional to the traditional row-based approaches data warehouses. Organizations are – and Sybase IQ supports most of the Sybase IQ centralizes “Big Data” analysis now able to support user communities popular hardware and OS configurations. of massive volumes of structured and across the enterprise, and integrate unstructured data together using a analytics into business workflows. And, Big Data is not new to Sybase. Sybase IQ wide range of advanced techniques it’s easy to leverage advanced analytics has been building on the vision of a big and technologies – offering a data type within applications by using hundreds of data analytics platform for several years agnostic engine Sybase IQ doesn’t care algorithms and data mining models that now – the new Sybase IQ 15 family has what format of data you have or even can run inside Sybase IQ. been a steady progression of releases where it came from. Whether it be Elastic computing of logical servers in the that have followed a conscious roadmap, structured in a defined format, semi- PlexQ™ technology framework within each one adding innovations that build structured available electronically, Sybase IQ allow IT staff to group together upon the foundation and strengths of unstructured requiring text mining or compute resources, in a PlexQ grid, into the previous release. Sybase IQ has been analytics tool extraction or web data, virtual groups in order to isolate the designed to meet the growing needs of such as, social media – it simply doesn’t impact of different workloads and users IT and Business Analysts to tame the matter with Sybase IQ. from each other. When a user connects to a logical server and runs a query, the SAP Sybase IQ - Turning Big Data into a Big Advantage is published by Sybase. Editorial supplied by Sybase is independent of Gartner analysis. All Gartner research is © 2012 by Gartner, Inc. All rights reserved. All Gartner materials are used with Gartner’s permission. The use or publication of Gartner research does not indicate Gartner’s endorsement of Sybase’s products and/or strategies. Reproduction or distribution of this publication in any form without prior written permission is forbidden. The infor- mation contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in enti- ties covered in Gartner research. Gartner’s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see “Guiding Principles on Independence and Objectivity” on its website, http://www.gartner.com/technology/about/ombudsman/omb_guide2.jsp. 2
  • 3. Figure 1: SAP Sybase IQ - A complete and comprehensive big data analytics platform Source: Sybase query execution is only distributed to For statistics and data mining Sybase IQ techniques such as network analysis or for member nodes of the logical server, and supports a DBLytix library from Fuzzy searching large amounts of unstructured member nodes can be dynamically added Logix containing hundreds of advanced data that is not indexed. or dropped as necessary. analytic, statistical and data mining algorithms that can run inside Sybase IQ. In addition to a native MapReduce Specialized Tools & API, Sybase IQ offers four ways to Techniques For text analytics Sybase IQ provides integrate results from 3rd party Hadoop comprehensive in-database text search frameworks into Sybase IQ queries, giving Sybase IQ has partnered with a number capabilities. With Sybase IQ’s key a tiered approach to analyzing massive of key advanced analytic partners in Analytics partnerships – both internal and data sets. In essence, massive volumes order to provide key in-database analytics external, such as, SAP BusinessObjects, of data can be searched from distributed techniques. Using in-database analytics ISYS and KAPOW, hundreds of document file systems. The data returned from a enterprises and application vendors can formats and Web content can be ingested Hadoop analysis can then be integrated answer complex questions without having and/or extracted into Sybase IQ for into a Sybase IQ database in any of the to move mountains of data to 3rd party analysis. four ways: tools. With hundreds of statistical and • ETL Processing, which bulk load data mining techniques, advanced text Sybase IQ provides a native MapReduce data from Hadoop data stores into analytics capabilities, and APIs to execute API that can leverage massively parallel Sybase IQ using the open source proprietary algorithms safely inside processing across a PlexQ™ grid. Using utility SCOOP from Sybase’s Sybase IQ, companies can gain insights in MapReduce allows you to move beyond partner Cloudera. unparalleled time. limitations with SQL queries, enabling • Data Federation, which exposes you to more easily execute alternative HDFS files as tables in a Sybase IQ database that participate in SQL 3
  • 4. queries (HDFS files do not need to to search and filter data for analysis in movement can impose severe constraints be loaded into Sybase IQ). combination with its column store engine. on timely delivery of the results you • Query Federation, allowing SQL Following the SQL Multimedia (SQL/ need to succeed and can account for up queries in Sybase IQ to execute MM) standard for storing and accessing to 75% of cycle time. By running analytic Hadoop processes that return data geospatial data, Sybase IQ supports 2D techniques inside the database Sybase that is incorporated into the SQL geometries in the form of points, curves IQ dramatically accelerates performance, result set, and finally. (line strings and strings of circular arcs), while avoiding governance and security and polygons. Sybase IQ also supports flat concerns caused by data movement. You • Client-side Federation, which and round-Earth representations, allowing need an analytics environment that can federates queries across Sybase you to choose the approach that best analyze large volumes of data from diverse IQ databases and Hadoop files addresses your situation. sources and provide fast, accurate results using the TOAD© SQL tool from - Sybase IQ’s in-database capabilities can Sybase’s partner Quest. Sybase IQ provides enterprises with APIs give you this advantage. to create proprietary analytic algorithms Use “R”, the popular open source that can run inside the Sybase IQ database Successful Analytics Platform statistical tool, to query Sybase IQ server for top performance. In particular, for Big Data databases using an RJDBC interface. Sybase IQ offers Java and C++ APIs, with Furthermore, you can execute R libraries these APIs you can create User Defined Sybase is on a mission to revolutionize Big from Sybase IQ as a function call within Functions (UDFs) that are called through Data Analytics with Sybase IQ. With our SQL queries and return result sets. SQL queries. The UDFs can access all of centralized data analysis delivering insights the data within a Sybase IQ database and across your Enterprise, and our support Sybase IQ also offers in-database can leverage a PlexQ™ grid for massively of large user communities running a wide execution of Predictive Model Markup parallel processing. Sybase IQ also offers range of analytics workloads – allowing Language (PMML) models through a an In-database analytics simulator, which organizations to analyze hundreds of certified plug-in from Zementis. This allows you to test a custom built UDF terabytes, even petabytes of data in allows you to automate the execution before deploying it into a production speeds up to 100 times faster – you can of analytic models defined using industry database. see that the big data challenges introduced standard language and that are created in SAS, SPSS Clementine, and other popular at the beginning of this article – volume, As you can see in-database analytics is a velocity, variety, costs and skills, are predictive workbench products. By using key component to Sybase IQ’s success in matched with the growing set features industry standard languages it enables being an advanced analytics platform for and capabilities offered by SAP Sybase IQ. you to leverage your existing investments Big Data. Data volume, accuracy, and swift Now with accurate complete information while providing better performance and processing time are all factors critical for across your enterprise, Big Data doesn’t scalability. success but the balancing act between seem like such a Big Problem it has turned these key components continues to pose into a Big Advantage – with SAP Sybase Within Sybase IQ, the row store SQL serious challenges for most organizations. IQ! Anywhere engine, allows you to also With traditional analytics this data create indexes of geospatial information Source: Sybase 4
  • 5. Gartner Reserch: Magic Quadrant for Data Warehouse Database Management Systems The data warehouse DBMS market used as a data warehouse – rather, a data data (SSED), excluding all data warehouse is undergoing a transformation with warehouse (solution/data architecture) design-specific structures (such as indexes, the introduction of “big data” and the is deployed on a DBMS platform. A data cubes, stars and summary tables). SSED logical data warehouse demand for new warehouse solution architecture can is the actual row/byte count of data techniques in practices and technology. and often does, use many different data extracted from all sources. The integration of professional services constructs and repositories. Importantly, From 2012 onwards, defining the size of with product offerings also increased in the definition of this market is changing a warehouse will become less important importance in 2011. and a DBMS will become only part of the and information asset access will become overall market definition as the logical more important. Within SSED it is Market Definition/Description data warehouse (LDW) continues to important to separate the actual data size This document was revised on 05 March grow in acceptance and deployment. in a data warehouse from the database 2012. The document you are viewing total size. Gartner clients report that is the corrected version. For more A data warehouse is a database in which many 100-terabyte warehouses often information, see the Corrections page on two or more disparate data sources can hold less than 30 terabytes of actual data. gartner.com. be brought together in an integrated, Throughout 2012 and 2013, the size of a time-variant information management warehouse will evolve toward a combined The supplier side of the data warehouse strategy. Its logical design includes the metric, relative to the repositories under database management system (DBMS) flexibility to introduce additional disparate direct management of the warehouse and market consists of those vendors data without significant modification complemented by the volume of available supplying DBMS products for the database of any existing entity design. A data information accessed by the warehouse, infrastructure of a data warehouse and warehouse DBMS is now expected to as well as its performance in doing so (see the required operational management coordinate virtualization strategies, as Note 3). controls. well as distributed and/or processing approaches such as MapReduce, to In addition, for the purposes of this For the purposes of this Magic Quadrant handle one aspect of big or extreme data analysis, we treat all of a vendor’s analysis, a DBMS is defined as a complete situations. products as a set. If a vendor markets software system that supports and more than one DBMS that can be used manages a logical database or databases A data warehouse can be of any size. The as a data warehouse DBMS, we note in storage. Data warehouse DBMSs are sizing definitions of traditional warehouses this fact in the section related to the systems that, in addition to supporting remain as: specific vendor, but evaluate its products the relational data model (extended to • Small data warehouses are less than together as a single entity. Further, a support new structures and data types 5 TB. DBMS product must be part of a vendor’s such as materialized views, XML and product set for the majority of the • Midsize data warehouses are 5 TB metadata-enabled access to content), calendar year in question. If a product to 20 TB. support data availability to independent or vendor is acquired mid-year, it will be front-end application software and • Large data warehouse are greater labeled appropriately but placed separately include mechanisms to isolate workload than 20 TB on the Magic Quadrant until the following requirements (see Note 2) and control year (see Figure 1). various parameters of end-user access Importantly, none of these categories within a single instance of the data. qualify a warehouse as a “big data” There are many different delivery models, warehouse. Volume alone is not “Big such as stand-alone DBMS software, This market is specific to DBMSs used data.” For the purpose of measuring the certified configurations, data warehouse as a platform for a data warehouse. It is size of a data warehouse database, we appliances (see Note 1) and cloud (public important to note that a DBMS cannot be define data as source-system-extracted and private) offerings. These are also evaluated together within the analysis of each vendor. 5
  • 6. Figure 1. Magic Quadrant for Data Warehouse Database Management Systems is either a visionary with cloud and data warehouse as a service, but does not execute against the challengers leaders rest of the market, or it is good at execution against two of the many use cases in the market with little Teradata vision for the remainder. Oracle The 1010data position is almost IBM perpendicular to our combined EMC/Greenplum evaluation criteria. Therefore, we ability to execute Sybase, an SAP Company have placed it with high execution 1010data against a sub-section of the market Microsoft we evaluate. From a visionary ParAccel Vertica perspective, 1010data is difficult Kognitio to evaluate under current criteria. SAND Technology Its approach in using a cloud- Infobright based and “as a service” DBMS/ analytics solution is the primary Actian business model and technology approach. Cloud-based analytics as a service and the ability to deliver Exasol under a managed on-premises niche players visionaries model, leaves 1010data short of the much broader vision desired completeness of vision by the greatest portion of the As of February 2012 data warehouse market, but in these few delivery segments of the Source: Gartner (February 2012) market 1010data is a formidable performance competitor. • 1010data is expected to add Magic Quadrant share large amounts of data without probabilistic matching in 2012. needing to manage it locally – for The company has exhibited Vendor Strengths and Cautions example, large quantities of CPG significantly more reduced load 1010data times than some of its significant data can be shared by multiple retail 1010data (www.1010data.com) was big data competitors, as well as companies. established 11 years ago as a managed orders of magnitude and faster service data warehouse provider with an As a managed service solution performance in extremely large integrated DBMS and business intelligence vendor, 1010data can complement datasets. 1010data products read (BI) solution primarily for the financial the customer’s internal IT SQL, but also utilize their own, sector and more recently, the retail/ department with fast-to-market non-SQL language that performs consumer packaged goods (CPG) sector. solutions for business units, so high-speed joins with unplanned 1010data can host its solution using reducing resource consumption data rationalization built into the traditional software as a service (SaaS) within the IT department. More queries without the performance model or support a managed solution importantly, the managed service disadvantages of using interim at the customer’s site. 1010data has model enables 1010data to leverage return datasets. approximately 200 customers. software solutions across multiple customers. As new applications are • Perhaps the most important Strengths created, they become available to point raised by those customers all clients, increasing the availability referenced is that 1010data is • Since 1010data offers a complete utilized by both IT and the business of these applications to businesses. SaaS solution, the customer’s with fast response times on queries With more than 200 customers, business unit and IT organization running against hundreds of billions 1010data has reached a position to need little experience of data of row tables (with a combined break out of its former niche status. warehousing or BI. The SaaS model number of rows throughout The problem is that the company also allows multiple organizations to 6
  • 7. databases exceeding a trillion rows As the demand for hybrid analytics Actian in the entire database in some mixing structured data with content Actian (www.actian.com) offers two instances). The company also increases, 1010data will need to products, the general-purpose Ingres serves as a data aggregator and data introduce unstructured data analysis DBMS and Vectorwise, a new offering marketplace providing datasets for as well as operational technology introduced in June 2010 and targeted at rapid enhancement and enrichment or machine-generated data analysis. analytic data warehouses. Open-source of analytics normally bound to 1010data’s competitors have greater Ingres, one of the original RDBMS internal datasets only. financial resources and already are engines, has a 30-year history and claims Our reference checks and in the process of building out this more than 10,000 customers running discussions with Gartner clients part of the data warehouse vision. mission-critical applications, including data also show that 1010data is • One of 1010data’s strengths warehouses. price-competitive with non-SaaS also acts as a caution. While the alternatives, especially by reducing business prefers a solution that is a Strengths the management overheads needed complete, deployment-ready stack, • The Actian database contains most to support a data warehouse IT departments and purchasing of the features necessary for data environment. 1010data has offices do not. 1010data’s offering is warehousing, such as partitioning, expanded from the financial sector sold as a fully integrated DBMS and compression, parallel querying (where it began) into a broader BI solution, which limits potential and multidimensional structures. market, including the retail sector. customers to those wanting a Release 10 added bulk load, scalar 1010data now claims more than full solution (primarily because subqueries, long identifiers and 200 customers and its customer of 1010data’s pricing model). a geospatial offering that was references support our belief that 1010data’s product is a compliant, community driven with hundreds it is one of the stronger small relational DBMS (RDBMS) that of committers contributing code. data warehouse DBMS vendors. customers can use as a stand-alone The performance of Vectorwise, In addition, the company has a system if desired – but fees are especially in analytic applications, small number of customers that charged as if the entire solution is was cited by customers interviewed install its system on-premises as managed. Customers are advised to by Gartner. With the emergence a managed solution, with several check the total cost of ownership of new server platforms with using 1010data as an enterprise in such cases, as it may not be storage-class memory (of 1 TB and data warehouse solution vendor. advantageous to use 1010data in more), Vectorwise will prove a Therefore, from an execution this way. valuable asset for data warehousing standpoint, 1010data matches • As a solution vendor, 1010data and analytics as more of the data performance, pricing and delivery has a different competitive warehouse moves to memory. model for two specific needs in model from vendors of pure-play • Actian has aggressively pursued the market quite well and it is DBMS offerings. In addition to partners, including independent expanding both its scope of delivery competing in the data warehouse software vendors (ISVs) in the BI and its vertical customer base. DBMS market, it competes with market, the primary driver of new system integration vendors that installations in data warehousing. Cautions offer outsourced solutions, such Both new and existing customers • The market continues to resist as Cognizant and HP (via EDS). are looking for an open-source fully-managed data warehouse Additionally, IBM, Oracle and other BI stack with partners such as services in many verticals and large vendors with professional Jaspersoft and commercial BI horizontal use cases. 1010data is service organizations compete with vendors such as MicroStrategy susceptible to resistance from IT 1010data in two markets, data have also engaged with Actian. departments requiring all its data warehouse DBMSs and services. It Ingres and Vectorwise are gaining warehouses to be located in-house, remains to be seen if this is a bias attention from vertical application along with in-house governance to be overcome or if the cloud vendors, system integrators and of the organization’s data assets. and on-premises mix will ultimately resellers. Vectorwise uses some The IT market is not fickle and exclude a vendor like 1010data. Ingres software atop a column store persists in its use of better name- However, based on its extremely from the MonetDB project and uses branded vendors and not simply positive customer references, it hardware assists, turning columns because they are name-branded. is very unlikely 1010data will be into vectors and processing them excluded from such a mix. in x86 chip registers to leverage 7
  • 8. instruction parallelism and on-chip • Actian offers professional services Strengths caching. Vectorwise has delivered in data warehousing and has a go- • Greenplum’s understanding and several top non-clustered TPC-H to-market strategy with a growing vision of the data warehouse benchmark results at 1 TB and stable of partners – it claims half market was ahead of the market as below. The company was renamed of its 2011 Vectorwise sales have it was one of the first to work with in late 2011 and introduced another come though channels. However, MapReduce, manage external files new product offering, the Cloud it lacks data models and must from within the DBMS and optimize Action Platform, to support the continue to add marketing and sales for very large database sizes. As delivery of “Action Apps” that expertise for data warehousing. big data is now important in the will act on the analytic capabilities Additionally, Actian has strength market and the LDW is emerging as Actian supports. in open-source, but the overall a necessary functionality to support • Previous reference checks have adoption of open-source for data today’s mix of volume, velocity, shown Ingres customers to be very warehousing remains weak. While variety and complexity, Greenplum loyal. Most have online transaction Actian has professional services, it has a base to support this that was processing (OLTP) applications, tends to lack some of the tools and launched several years ago, which but Ingres has also been used methodology support that other translates into the high ability to for smaller data warehouses organizations have readily available. execute. (historically up to about 2 TB, the • Actian’s new brand and name, as Greenplum announced the first company is targeting warehouses well as its portfolio expansions, can unified analytics appliance addressing smaller than 10 TB). Among open- help overcome Ingres’s reputation big data (a modular solution for source DBMS, only Oracle’s MySQL as an older product that has not structured and unstructured data), compares with proven maturity regained much market traction. in May 2011 that was released for mission-critical applications, Importantly, Actian has taken a bold in September 2011. The EMC including data warehousing. stance in attempting to re-establish Greenplum Data Computing Vectorwise has begun to gain new itself with a new vision and new Appliance (DCA) uses the customers and software partners, plans for execution. Initial response Greenplum Database, Greenplum targeting another set of use cases. to Vectorwise is significant with the HD (Hadoop), and Greenplum Now in its version 2.0, it has added addition of more than 20 customers Data Integration Accelerator (DIA) Windows as a platform and has a in its first year offering and users modules that can be configured clear road map for several future should consider Actian’s Vectorwise within one single appliance cluster. releases. to be a new and innovative In addition, Greenplum has Chorus, solution in that respect. However, its analytics productivity software, Cautions market perception is difficult to leveraging VMware’s technology, to change. Both offerings have gained support automated, self-service data • Although Vectorwise enhances new customers and third-party services and collaborative analytics. Actian’s ability to support analytic relationships, but to become a In a recent announcement, EMC data marts, the company must serious competitor in this market announced the first Hadoop NAS continue to address enhanced data Actian must continue to show attached HDFS system – HDFS warehouse functionality, storage increased growth in both revenue running native on EMC Isilon management and mixed workload and numbers of new customers at connected to the Greenplum HD management if it is to compete a higher rate than it has thus far. or Greenplum Data Computing with larger, equally mature vendors Effective marketing execution is a Appliance (DCA). Finally, through and meet the needs of the broader must-have for Actian to compete. the external file mechanisms and data warehouse DBMS market. Vectorwise needs to support more user defined functions (UDF), analytic SQL constructs than it does EMC/Greenplum Greenplum has started along the now and add stored procedures Greenplum (www.greenplum.com) is part path to support LDW. Greenplum and user-defined functions and of the Data Products division of EMC even supports an iOS, Linux and data types to move closer to with a massively parallel processing (MPP) Windows single-user development competitors. Its new product and data warehouse DBMS running on Linux system downloadable as free (not restructuring around Action Apps and Unix. It can be sold as an appliance or open-source) software. can be synergistic – but could also as a stand-alone DBMS and has more than • As Greenplum has settled into prove distracting. 400 customers worldwide. the EMC organization, we have 8
  • 9. seen an increase in hiring directly presence to compete with all the Exasol related to development. This, incumbent, large DBMS vendors. Exasol (www.exasol.com) is a small DBMS coupled with the EMC development Importantly, EMC’s customer base vendor in Nuremberg, Germany. Exasol organization has led Greenplum is primarily within the IT unit of has been in business since 2000 with the to offer its DCA supporting big the organization. Data warehousing first in-memory column-store DBMS, data for both structured and is the technical infrastructure for EXASolution, available since 2004 and unstructured data and intergraded an intensely business-oriented primarily used as a data mart for analytic MapReduce processing. The DCA use-case. EMC will need to learn applications. is now assembled by EMC and sold from its Greenplum acquired by its sales force. In an interesting knowledgebase, specifically how to Strengths manufacturing cost management solution sell a data warehouse and • Exasol offers an in-memory column- model, EMC is assembling its analytics solution. store DBMS for data warehousing. appliances in different countries • Interestingly, this year our customer As we have stated, this technology around the world, affording EMC references have raised several is one of the critical capabilities of Greenplum a tax advantage in many issues around support. In these the future for the data warehouse countries where others (such as cases it was not related to the DBMS market. Exasol runs in a Oracle and Teradata) are subject attention to rapid support and clustered environment offering to stiff import duties. This positions fixes (with all customers stating scalability across multiple servers. the company for easier entry fixes were available in an expected, Not only does this allow for high- into global markets. Due to the timely manner), but more with availability in the case of a server acquisition, Greenplum has been the bugs in the first place. We failure using EXACluster OS, but able to work more closely with would classify these as “growing also scaling for larger memory sizes. VMware, for example rearchitecting pains” especially for a small EXASolution maintains redundant the Chorus private cloud offering. organization (as Greenplum was copies of the data in memory to • Our customer references support pre-acquisition) being integrated reduce the downtime associated the claims of high performance into a large organization such as with server failures. as well as advantageous price/ EMC. We should also note that in Exasol also includes the use of disk performance ratios. These our inquiries with Gartner clients, for persistence and overflow (if all references also support the we have seen this issue diminish, the data does not fit in memory). Greenplum claim of scalability to coupled with consistently high However, when data is loaded into very large database sizes. Reported marks for personalized customer Exasol, it is loaded into memory sizes range from 10 terabytes to support. first and then written to the disk, more than 500 terabytes. When • As Greenplum leverages EMC allowing for the applications to this combination of performance more, it will find itself competing begin before the slower activity and scalability are joined to an at a higher level with the mature, of disk input/output (I/O) is appliance, the potential of EMC/ incumbent vendors. The major completed. This separation of the Greenplum to compete in the data vendors (such as IBM, Oracle, SAP data access and data persistence warehouse market is increased. and Teradata), have a much larger model is a visionary change for the customer base allowing them, as market. Additionally, as a column- Cautions the incumbent, a stronger position. store, Exasol has excellent data • Although acquired by EMC 18 EMC/Greenplum must continue compression (reported to be on months ago and despite doubling to demonstrate differentiation as average, four times faster), thus the install-base, Greenplum’s it addresses the data warehouse reducing the amount of memory market position is sixth or seventh market and big data is one specific necessary. EXASolution is sold by worldwide. To really increase area, as is cloud. The company must the amount of memory used for the velocity and gain market share, continue to support customers data. Greenplum must continue to accustomed to the type of service • Another advantage of Exasol, as develop the EMC sales force so provided by a small company with other in-memory DBMSs, is that it has the necessary skills with focused, customer-specific the high speed of the DBMS. In in the DBMS software market. professional services solutions, published benchmarks, Exasol has Greenplum must also continue issue-focused support and leveraging attained data warehouse transaction to leverage the EMC worldwide key customer inputs for product speeds up to 20 times the closest enhancements. 9
  • 10. competitor. Server memory Exasol lacked a marketing vision vendors such as Quest are less is expensive, but these same to grow beyond the borders of its likely to support the DBMS, benchmarks demonstrated costs European base. The company began requiring Exasol to create their own of approximately one-third of the an expansion plan in 2011 and management software. standard DBMS. Our reference will begin to grow offices in other checks also validate the claims of locations, including North America. IBM cost reduction and speed. Another • Another issue is the increasing IBM (www.ibm.com) offers stand- strength of the in-memory nature competition, both in column-store alone DBMS solutions as well as data of Exasol is removing the necessity and in-memory. Exasol has a clear warehouse appliances, currently marketed of optimization and calculation advantage being the first with an as the IBM Smart Analytics System family structures within the database. in-memory column-store DBMS. (ISAS) and the Netezza brand. IBM’s There is no need to build Now, most of the DBMS vendors data warehouse software, InfoSphere summaries, aggregates and cubes offer some form of column-store Warehouse, is available on Unix, Linux, for use in business intelligence capabilities. Further, when Exasol Windows and z/OS. IBM has also and analytics. This reduces the began, there were only a handful of continued research and development and overhead in the DBMS by as much in-memory DBMS, mostly used for market execution for the Netezza brand as 10 times, as well as reducing streaming data applications. There and product line following its acquisition. the database administrator (DBA) are now many in-memory DBMSs IBM has thousands of database customers resources used to maintain such available in both the column and worldwide and more than 500 appliance structures. In addition, this also row-store variety. Finally, SAP has customers (Netezza and ISAS combined). leads to very fast load times, released its SAP HANA appliance as there are no complicated with an in-memory column-store Strengths structures to build during loading. DBMS for an analytics data mart • The breadth of IBM technology • Customer references clearly and now available under the SAP offerings is complementary to espouse the abilities of NetWeaver Business Warehouse. and part of its solution delivery EXASolution for both pure As with many technologies, capability. InfoSphere Warehouse, performance and cost/performance. being first is not sufficient unless a data warehouse offering based The references (although few in capitalized in growth of market on IBM DB2, is a software-only number) also state that customer share. Exasol has missed the solution. IBM’s data warehouse support is excellent. Finally, window of opportunity of being appliance solution, the IBM references corroborate the results first and now faces increased Smart Analytics System (ISAS) is of the benchmarks mentioned competition. a combined server and storage here, with better than 20 times • Customer references report that hardware solution (using the IBM performance at half to a third there is one major issue with the Power Systems server with AIX, of the cost. They also support use of EXASolution – the lack of the System x server with Linux or the claims of 4 times (or more) interfaces to common BI tools. Windows and the IBM InfoSphere compression. Exasol offers the standard ODBC Warehouse and a robust System and JDBC interfaces, but this can z ISAS data warehouse solution), Cautions be a performance drawback with complete with service and support. tools such as BusinessObjects, • The primary challenge Exasol faces IBM’s introduction of InfoSphere Cognos and SAS. As Exasol has a is the small size of the company and BigInsights includes offerings to aid small installed base, it is difficult to previous lack of expansion beyond the design, installation, integration engage the tools vendors to assist Germany. Exasol was primarily and monitoring of the use of in creating native interfaces to the engaged in product development Hadoop technologies within an DBMS. We do expect to see this for its first five years of operations IBM-supported environment. In remedied over the next few years and with changes in management IBM’s case, it is important to note as the size of the installed base two years ago has now obtained that it has embraced the vision grows. Similarly, there is a reported the vast majority of its 30 or more for the LDW – which Gartner lack of software to manage the customer base in the past two describes as the emerging new best Exasol environment (EXASolution). years. These customers are mostly practices in analytics management. Again, with a small installed base, located in Germany, with several in By tying together relational data, third-party management software Italy and Japan. Until very recently, data streams and Hadoop files, 10
  • 11. IBM’s stack builds confidence among IBM specifically assigns technical own methodology and highlights managers of existing warehouse account managers to support that the traditional enterprise data implementations that the product is accounts). Additionally, IBM’s focus warehouse [EDW] is vital to all data evolving as new demands for these on prospect qualification resulted in warehouse strategies including as a two components of the logical data a higher growth in 2011 vs. 2009 to base component for the LDW. warehouse emerge. 2010 for all of its products. This was IBM’s first incarnation of Additionally, for Smart • The overall effect is that referenced the LDW approach. The market Consolidation – rather than customers are confident regarding is acknowledging that the EDW developing tooling in isolation, IBM release dates and the road map. does not have to be the center of focused on tooling that existed in Customers list concurrency, the strategy but will be significant. its Information Integration portfolio scalability, performance optimization However, the justification for (InfoSphere BluePrint Director). and support as positives and were the LDW and evolving existing This resulted in improvements in the most often repeated phrases warehouses or replacing them the area of integration, including but in the reference survey in 2011. will be difficult at first because not limited to the common Data References elaborated by indicating it appears to supporters of Warehouse Packs and Models now that partitioning, compression and traditional data warehouses to supported on DB2 and Netezza reduced administrative hours all be a radical departure from their platforms alike. contribute to their experience to beloved traditional data warehouse • IBM combines product sales with support optimized performance. practices. Gartner’s own research solution services. This market At the same time, some references indicates that the LDW approach is demands a widely varied level reported that optimization of quickly emerging as the newest data of sophistication and knowledge queries should be targeted rather warehouse best practice. Gartner depending on each client than being forced to optimize every anticipates the LDW will become organization’s maturity in analytics single query because the system is a best practices approach during and information management. As able to engage a solid query plan for 2013-2015. With market leadership noted in the overview, the data execution. This evaluation considers there is risk commensurate with the warehouse market in 2011 has the LDW concept to be innovative, anticipated rewards. IBM will need multiple visions for the future. but has yet to see a wider embrace to continue their careful education IBM has embraced the logical in the market. IBM’s early adoption message regarding their leadership data warehouse (via “Smart of the LDW concept in both its approach in LDW practices. When Consolidation”) approach while messaging and its product road engaging in an LDW approach continuing to advance its technology map has established this vendor as with IBM, clients should insure solutions and implementation an early resource for the market. they completely understand IBM’s practices supporting traditional data However, the majority of the positioning for implementing this warehousing architectures. market for data warehousing will solution. Professional services available remain significantly focused on • Gartner inquiries report indicate from IBM range from expert traditional solutions for a minimum that IBM data warehouse solutions education through turnkey of the next three years. are also marketed and delivered in solutions to managed services for isolation from each other. There are data warehousing. Importantly, Cautions strategic reasons to continue such where IBM leverages its services an approach with any acquisition, • IBM has embraced the logical data organization most, is in feeding but Netezza products tend to have warehouse vision as the likely field experiences into the overall their own niche in customers’ minds successor to current best practices data warehouse vision. In 2010, that is viewed as being separate and in traditional data warehousing. The clients reported that IBM’s support distinct from IBM (but Netezza’s market has not yet determined if appears disconnected from its growth was more than 30% in 2011, it is ready to adopt this approach product strategy – this improved in which is faster than its previous as the new vision for the data 2011 with an even larger reference growth rate as an independent warehouse and abandon 20 years base reporting. This does not mean company). of traditional best practices. the issue has been resolved, but it IBM’s professional services have As a result, IBM customers often appears that IBM’s focus on solution experience in delivering various engage only part of the organization services is paying off (for example, aspects of the LDW under its for solutions and at least in the 11
  • 12. customer’s minds, eliminate the compressed DBMS. The company Infobright also released an option others. This creates both marketing provides both an open-source version for the Enterprise Edition called the and sales process challenges. This (Infobright Community Edition [ICE]) Distributed Load Processor (DLP) is not an issue with shortlisted and a commercial version (Infobright which allows for the parallel loading solutions (IBM should recommend Enterprise Edition [IEE]). Infobright has of data into the system at very high one solution or another), but does approximately 200 customers worldwide. speeds. Infobright has also added carry over into the solution delivery connectivity to Hadoop MapReduce team and IBM is missing some Strengths for the processing of “Big data.” opportunities for the different parts • Infobright remains one of the only This is extremely important to of the sales organization to leverage column-store DBMS in the open- the machine-generated data world each other. IBM has implemented source software environment. as much of this data is stored in organizational changes intended to Its revenue is generated from Hadoop or other such file systems address these issues. the Enterprise Edition (using a and needs to be extracted into a Netezza and IBM personnel do commercial license, rather than a DBMS for processing. interact and coordinate with General Public License [GPL]) with • Our customer references are clear each other behind the scenes. a subscription support model based on several points. Infobright is A marketing solution would on the amount of SSED stored in extremely fast compared to other simply begin branding software the system. As we stated in 2011, systems, including MySQL. Reports and hardware combinations for Infobright decided in mid-2010 to of up to an average 500% increase limited purposes. However, IBM focus on operational technology in performance over MySQL will choose the more difficult (and data (which it calls machine- deployments have been reported. more appropriate) solution of generated data). This encompasses We believe this is not only from creating an educational sales and data from sources such as smart the column-store design, but also implementation process which meter data (in the utilities space), the Knowledge Grid. References will demonstrate how software customer data records (in the telco suggest that Infobright is replacing and hardware capabilities can be space) and clickstream data from an existing MySQL environment leveraged effectively to support Internet interactions. with great gains in stability, each use case. This focus has helped Infobright compression and performance. • IBM customers report (via inquiry during 2011 where its customer Some cases report a year or more and reference survey results) base has grown to more than 200 without an outage. a scattering of intermittent direct and OEM channel customers. Finally, many references state that and irregular issues with Not only has this focus increased simplicity is a factor in their choice product performance or their customers, but has also attracted to use Infobright. We also believe implementation experience. Some a number of additional OEMs this will interest OEMs that want to of these are possibly attributed to (now accounting for approximately build-in Infobright to their existing the implementation process and 40% of customers). This, along systems for resale. The simplicity not the products. However, these with partnerships with Pentaho, of management, scalability and same customers report that IBM Jaspersoft, Talend and others, will compression all interest the OEM support addresses these issues with help the company grow substantially looking for a DBMS to embed that efficiency. Nonetheless, as with faster than direct sales only. requires little support on their part. any IT products, an assumption • Infobright has several unique The focus on machine-generated that appliances or certified technologies in the DBMS. In data has been important to configurations alleviate all issues is addition to the column-store file Infobright, but we believe that the incorrect. Most issues are irregular system for MySQL, the Knowledge future will greatly depend on the in nature and IBM support is Grid in-memory metadata store company’s ability to leverage these intimately involved in the resolution is a major differentiator for OEM partners. process. Infobright, as this product analyzes queries to minimize the number Cautions Infobright of “data packs” that have to be • One of the biggest challenges for Infobright (www.infobright.com) has decompressed to give a result (data a small vendor is to focus on what offices in Canada, Europe and the packs are the compressed domains/ they do well. Infobright has done U.S. and offers a combination of a regions of data in Infobright’s this with machine-generated data. column-vectored DBMS and a fully offering). 12
  • 13. However, as a small, relatively MySQL. To date, Oracle has not started to produce results, with young vendor, Infobright must done anything other than enhance several new customers. Kognitio continue to differentiate its the product. However, in the future has also added several hosting offerings and open-source model when the contract is done with EU, partners in the U.S. and the U.K. from mature column-store DBMSs. we cannot guarantee that Oracle offering managed services on WX2. Sometimes, these two statements will not change the agreements, Its sales model as dbSaaS makes up are contradictory not least because especially those with OEMs. This almost half of its revenue and has the focus on machine-generated is an issue customers of Infobright supported much of the company’s data cannot be an excuse for should monitor in the future. growth this year. ignoring its existing customers • Kognitio continues to invest in addressing other data management in-memory capabilities. Gartner Kognitio use cases, reported in several considers that in-memory DBMSs Kognitio (www.kognitio.com) started by customer references as an issue. An can play a major role in enterprises offering data warehouse appliances and example is workload management information infrastructure and as warehousing as a hosted service. Today, software, where the managed such Kognitio’s technology has it has a mixture of less than 50 customers workloads are basically for machine- an opportunity to meet customer using its DBMS (WX2) separately as an generated data and may lack the demand, given the maturity of its appliance, a data warehouse DBMS engine, robustness needed for management offering, compared to other more or data warehousing as a managed service of overall workload. recent offerings. Kognitio’s DBMS, (hosted on hardware located at Kognitio’s • There are other issues raised by sites or those of its partners). WX2 version 7, already includes our reference checks. As with most in-memory analytics, and customer small startup vendors, stability from Strengths references continue to report one release to another can suffer. that the speed of query and load • Kognitio pioneered the data Customer references reveal that performance is excellent. In 2011, warehousing database as a service there have been issues with new Kognitio added Pablo in-memory (dbSaaS) model, where a data releases, but they are quick to point online analytical processing (OLAP) warehouse DBMS is delivered out that the problems are quickly capabilities to further strengthen its as a managed service from the resolved. The lack of management analytical capabilities The DBMS is DBMS vendor. Clients buy data software (also an issue for smaller already an in-memory DBMS, with warehousing services from Kognitio, vendors) was raised. Third-party hot data held in-memory and cold while Kognitio hosts the database. software vendors are not quick data on disk, managed automatically Data warehousing dbSaaS permits to pick up new, young software by the DBMS. clients to expand their warehouses companies, as the potential market • Those customers referenced incrementally and clients note is small, so this puts more pressure reported significant concurrency that this model provides for low on Infobright to produce its own capabilities, as well as excellent upfront costs with virtually no management software. support and product management. capital expenditure required to • Finally, Infobright is open-source get started. This is a growing Kognitio is gaining visibility thanks and makes use of portions of segment of the data warehouse to the current market interest in MySQL, under a Commercial OEM DBMS market. Kognitio also works in-memory technologies. Kognitio’s License with Oracle. We always with deployment partners such customers report that deployment question the open-source model as Capgemini (and contributes of large-scale data warehouse for revenue generation. First, to Capgemini’s Immediate cloud efforts takes as little as 10 weeks Infobright has a community version computing offering). using this model. References also with less functionality than the report predictable, linear scaling of Additionally, in line with existing Enterprise Edition. This has proven performance and under the “as a market demands, Kognitio has useful as a trial system to attract service” model, customers report an appliance to install on-site for new customers, but some may opt scale up and scale down needs as customers requiring their own for the ICE version in lieu of the part of a solid account management infrastructures. Kognitio opened Enterprise Edition. approach. Finally and possibly most offices in the U.S. three years ago The other issue is specifically the importantly, references indicate that in addition to its U.K. headquarters use of MySQL, as it is owned by new queries and new variations on and has continued to expand its Oracle. This implies risks remain existing analytics can be deployed presence in the U.S. by hiring due to the uncertain future of rapidly. additional resources. This has 13
  • 14. Cautions such as those of IBM (Cognos) can also leverage SharePoint and • Kognitio has a very substantial and SAP (BusinessObjects), is PowerPivot and the ability to opportunity in the small or midsize difficult to manage. This problem include an unstructured information business data warehouse and is compounded by Kognitio’s type in analytics is the result of BI market thanks to its dbSaaS small market penetration and the its technology blend and this is a model. However, over the past resulting scarcity of tool expertise strength that should definitely not year, managed services offerings in the market. References also be ignored. from IBM and HP/Vertica have report the absence of any form of • References report that Microsoft experienced growing acceptance developers’ forum or marketplace, exhibits one of the best value and penetration in the market. scarcity of skills in the market and propositions on the market with These offerings are not direct an extremely lean global presence a low cost and a highly favorable competitors to Kognitio’s solution, makes commitment to the product price/performance ratio. Skills are but the customer base views them and consistent delivery difficult. widely available in the marketplace as an equal alternative from more to operate a Microsoft data established vendors. Microsoft warehouse and there is an easy Kognitio has not yet addressed Microsoft (www.microsoft.com) continues learning curve to acquire those some of the very large volume to market its SQL Server 2008 DBMS same skills, as needed. As an added or variety of data support issues (Release 2) Business Data Warehouse bonus, customers report that the – more specifically support for and Fast Track Data Warehouse for data integration and continuity of a content and complexity aspects of warehousing customers not requiring an complete Microsoft data warehouse extreme information. However, MPP DBMS. Microsoft released its own and business intelligence stack is Kognitio’s in-memory analytical MPP data warehouse appliance, the SQL highly advantageous to time-to-value capabilities can be of value in low Server 2008 R2 Parallel Data Warehouse in delivery. Noticeably absent are latency, high volume analytics. (Microsoft) (PDW), in November 2010. any fears regarding vendor lock-in. The market shifted dramatically Strengths According to our reference checks during 2011 toward a new position. and discussions with our clients, • Microsoft spent 2011 revitalizing Kognitio did not stand still, but worldwide support from Microsoft its vision for the data warehouse market demand regarding new is extensive, encompassing partners, market. Additionally, it announced functionality expanded more rapidly value-added re-sellers, vendors of two Apache/Hadoop connectors than Kognitio’s product feature third-party software and tools and for SQL Server, SMP and Parallel sets. This appears to only be a widely available SQL Server skills. Data Warehouse (PDW) in temporary condition while Kognitio support of the market’s big data • Microsoft references indicate a addresses these new expectations. issues. Many would be surprised dominant presence in midsize data • While Kognitio continues to grow to learn that Microsoft already warehouses —especially those its installed base (with an additional provided combined structured end-user organizations reporting seven clients in 2011) the company and unstructured analysis in SQL that their companies and their data remains a small vendor with fewer Server 2008/R2. A third quarter management needs are growing. than 50 customers worldwide. appliance update included support According to customer references, This makes it increasingly difficult and enhancements for integration Microsoft assures its customers of to sell to organizations that have with SAP/Business Objects, a solid data warehouse platform incumbent vendors, and to compete MicroStrategy and Informatica. including features and functions with some of the lower-priced that run the gamut of traditional In addition, Microsoft offers the appliance offerings. Additionally, warehouse functionality. SQL Server Fast Track Data as a data warehouse outsourcing Warehouse, which includes For connectivity in a multi- solution, organizations should be validated reference architectures vendor environment Microsoft aware that they are still responsible for building a balanced data offers a SAP/BW, Teradata and for contracting and auditing data warehouse infrastructure. This Oracle connector. The DBMS security procedures. road map contributes significantly supports compression and • Clients report interoperability to the company’s vision for the backup compression, partitioned with third-party popular BI tools, market and its customers. Microsoft table parallelism, policy-based 14