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Big Data in the Enterprise.
When to Use What?
Jesus Rodriguez, Tellago, KidoZen, Inc
Agenda
• Big Data principles
• The Hadoop ecosystem
• Other big data technologies
About Me
• Co-Founder Tellago, Inc
• Co-Founder KidoZen, Inc
• Microsoft MVP
• Architect Advisor
• Investor
• Speaker, Author
• http://jrodthoughts.com
• http://weblogs.asp.net/gsusx
• http://kidozen.com
About Tellago
• Application development firm focused on big enterprise trends (launched
2008)
• Enterprise mobility, cloud computing, augmented reality, modern BI &
big data
• Advisor to software companies such as Microsoft or Oracle
• American Business Awards(2011) “Best Overall Company of the Year < 100”
• American Business Awards(2012) Silver: “Best Computer Services Company
of the Year < 100”, Silver: Best Computer Services Executive of the Year
• Inc 500 (114) & other industry awards
Some Housekeeping Rules
• Tellago Technology Updates focused on modern enterprise software
trends
• Real world stories
• No sales pitch
• Leverage GTW to ask questions
We Love Data!
Where all Started?
CAP Theorem
Big Data Opportunity
The Landscape
Or a Bit More Crowded
Or Worse
Hadoop Led the Way
Hadoop Design Principles
• System Shall Manage and Heal Itself
• Performance Shall Scale Linearly
• Compute Shall Move to Data
• Simple Core, Modular and Extensible
The Solution: HDFS + Map Reduce
Mapping
Hadoop Ecosystem
HDFS
(Hadoop Distributed File System)
HBase (key-value store)
MapReduce (Job Scheduling/Execution System)
Pig (Data Flow) Hive (SQL)
BI ReportingETL Tools
Avro(Serialization)
Zookeepr(Coordination)
Sqoop
RDBMS
(Streaming/Pipes APIs)
Reducing
HDFS
Map-Reduce
Relational vs. Hadoop
The Hadoop Ecosystem
WebHDFS
Sqoop
Flume
HBase
Pig
HCatalog
Hive
Ambari
Oozie
Zookeeper
Hadoop Enterprise Architecture
Hadoop is not a silver bullet...
Some Challenges
• Hadoop doesn’t power big data applications
• Not a transactional datastore. Slosh back and forth via ETL
• Processing latency
• Non-incremental, must re-slurp entire dataset every pass
• Ad-Hoc queries
• Bare metal interface, data import
• Graphs
• Only a handful of graph problems amenable to MR
Beyond Hadoop
• Percolator(incremental processing)
http://research.google.com/pubs/pub36726.html
• Dremel(ad-hoc analysis queries)
http://research.google.com/pubs/pub36632.html
• Pregel (Big graphs)
http://dl.acm.org/citation.cfm?id=1807184
Important Big Data Technologies in the
Enterprise
Real Time Analytics
Real Time Analytics
• Storm
• Hstreaming
• StreamBase
• IBM Streams
• Microsoft StreamInsight
MPP: Massively Parallel Processing
MPP Columnar Stores
• Oracle Exadata
• IBM Netezza
• Teradata
• EMC Greenplum
• HP Vertica
• ParAccel
• Microsoft SQL Server PDW
Oracle & Big Data
Microsoft & Big Data
NoSQL DBs
NoSQL DBs
NewSQL DBs
New SQL / Cloud DB
• VoltDB
• NimbusDB
• SimpleDB
• NuoDB
• Clustrix
• Totutek
Traditional BI Suites
New SQL / Cloud DB
• Hadoop Support In:
• Microsoft SSIS
• Informatica Datastage
• Talend
• Pentaho
• Microstrategy , SaaS
• Tableau, Qlikview
Big Data & Cloud
Big Data & Cloud
• Hadoop distributions (AWS, Microsoft HDInsight, Cloud Foundry)
• Data marketplaces (Factual, Infochimps)
• Data visualization (WibiData)
• NOSQL as a Service (MongoHQ)
If you are interested on evaluating Big
Data in your organization
Tellago Big Data Strategy Session
• 1 day strategy session
• Start with a real world scenario
• Explore various big data technology vendors
• Present a potential technology roadmap
• Free
• Emails us at info@tellago.com
Summary
• The big data ecosystem is super crowded
• Hadoop distributions are leading the way in the enterprise
• Complementary technologies include:
• NOSQL
• New SQL
• MPP
• Data Visualization
Thanks
jesus.rodriguez@tellago.com
http://www.tellagostudios.com
http://jrodthoughts.com
http://twitter.com/#!/jrodthoughts
http://weblogs.asp.net/gsusx

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