We live in the Age of Data. Now more than ever, it is crucial that organizations can connect, analyze and act on the vast amounts of data that surrounds them in order to succeed long-term. This session will discuss the Age of Data and how companies can deploy technology such as Actian ParAccel SMP, a fast analytic database platform that runs on standard hardware, in order to run sophisticated, unconstrained analytics on massive amounts of data (structured, unstructured, Hadoop etc) and turn their data into business value. Christian Raza - Director of Sales SEMEA, @Actian Corporation Actian presentation during the Pentaho & Big Data Ecosystem - Live Seminar 2013

1. Christian RAZA
SEMEA Sales Director
christian.raza@actian.com
Actian Vectorwise
Simply Fast = High performance + Affordable Cost
XpandIT / Big Data ecosystem / November 27 2013

2. Our Vision
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3. The Age Of Data
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4. The Age of Data
• “Data are becoming the new raw material of
business.“
Craig Mundie, Microsoft
•
“Data tap has been turned on and will never
be turned off.”
Mike Hoskins, Actian CTO, 2013
• “You can have data without information, but
you cannot have information without data.”
Daniel Keys Moran, Writer
• “It is a capital mistake to theorize
before one has data.”
Sherlock Holmes, Sir Arthur Conan Doyle
• “Torture the data,
and it will confess to anything.”
Ronald Coase, Economics, Nobel Prize
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5. Actian Big Data Platform
• “Data is the new oil.“
Clive Humby,
ANA Senior marketer’s summit
• “Information is the oil of the
21st century, and analytics is
the combustion engine.”
Peter Sondergaard,
SVP at Gartner
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6. Actian Big Data Platform
Operational Data
Big Data
Reservoir
Reporting
Applications
Analytic
Applications
Big Data pipeline
Search Based
Applications
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Graph Based
Applications
Open Data
Shared Data
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7. Extreme Reporting
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8. Extreme Analytic
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9. Actian Vectorwise
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10. Why Vectorwise?
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11. Vectorwise: started with an academic project
1990
1993
first
colomn store DBMS
MonetDB
2005
MonetDBX100
2010
Vectorwise
• Patent USPTO #20100235335 (Peter BONCZ):
Column-store database architecture utilizing positional delta tree
• Partnership with academic
• multi-core parallelism
•
just-in-time compilation of predicates
• non-intrusive query execution on compressed data
• cooperative Scans
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12. Vectorwise
New generation
Colummn DBMS
In CPU acceleration
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Ingres modules
encapsulation
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13. Vectorwise: simplified technical integration
 Connectivity
• .Net, JDBC, ODBC, PHP, Perl…
• ETL: Stambia, Talend, SyncSort, Informatica,
DataStage…
•
BI: BiBoard, BO, Cognos, MicroStrategy, Hyperion,
JasperSoft, Pentaho, SpagoBI, TableauSoftware,
YellowFin,…
•
Analytics: SAS, SPSS, RapidMiner,
RevolutionAnalytics,…
 Standard SQL
• No proprietary SQL
• Support de ANSI SQL-92
 DBA tools
• Actian Director
• BackUp / Restore
• Utilitaires Load/Unload (copy, vwload)
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14. Benchmark
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15. Benchmark TPCH : 3 world records
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16. Benchmark TPCH: Vectorwise VS MS SQL Server
MS SQL Server
TPCH 1TB
Ingres VectorWise
CPU Type:
Intel Xeon Processor E7-8870
2.40GHz
Intel Xeon E7-8837 2.67GHz
Server:
IBM System x3850 X5 8P
Dell PowerEdge R910
Total # of Processors:
8
80
Total # of Cores:
Operating System
Total Storage/Database Size Ratio:
Price/Performance
Availability Date
32
Microsoft SQL Server 2008 R2
Enterprise Edition
Microsoft Windows Server 2008 R2
Enterprise Edition
Database Manager
Metric
4
VectorWise 1.6
RedHat Enterprise Linux.6.1
7.00
2.34
173,962 QphH@1000GB
436,789 QphH@1000GB
1.37 USD per QphH@1000GB
.88 USD per QphH@1000GB
20-May-2011
© 2013 Actian Corporation
30-Jun-2011
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17. Benchmark TPCH: Vectorwise VS Oracle
Oracle
TPCH 1TB
Ingres VectorWise
CPU Type:
SPARC64 VII+ 3000MHz
Intel Xeon E7-8837 2.67GHz
Server:
SPARC Enterprise M8000 Server
Dell PowerEdge R910
Total # of Processors:
16
64
Total # of Cores:
4
32
Database Manager
Oracle Database 11g R2 Enterprise
Edition with Partitioning
VectorWise 1.6
Operating System
Oracle Solaris 10
RedHat Enterprise Linux.6.1
Total Storage/Database Size Ratio:
Metric
Price/Performance
Availability Date
11.20
2.34
209,533 QphH@1000GB
436,789 QphH@1000GB
10.13 USD per QphH@1000GB
.88 USD per QphH@1000GB
22-sept.-11
© 2013 Actian Corporation
30-Jun-2011
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18. Benchmark TPCH: Vectorwise VS SybaseIQ
Sybase IQ
TPCH 1TB
Ingres VectorWise
CPU Type:
AMD Opteron 8439 SE 6-Core 2.8GHz Intel Xeon E7-8837 2.67GHz
Server:
IBM Power 780 Model 9179-MHB
Total # of Processors:
Dell PowerEdge R910
8
48
Total # of Cores:
4
32
Database Manager
Sybase IQ Single Application Server
VectorWise 1.6
Edition v.15.1 ESD #1
Operating System
Red Hat Enterprise Linux 5.3
Total Storage/Database Size Ratio:
Metric
Price/Performance
Availability Date
RedHat Enterprise Linux.6.1
15.18
2.34
102,375 QphH@1000GB
436,789 QphH@1000GB
3.63 USD per QphH@1000GB
.88 USD per QphH@1000GB
01-Feb-2011
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30-Jun-2011
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19. Reporting / Dashboard
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20. Customer Benchmark: Vectorwise VS Teradata
o This performance benchmark was performed by Leroy Merlin France to evaluate
DBMS during a massive workload (load test duration: 1 hour).
o The target workload represents the reporting/dashboard activity of 10 000 sales
force between 08:00 and 09:00 AM of.
The peak workload was estimated at 600 concurrent users which gives 1200 queries
per minute.
o Vectorwise VS Teradata benchmark:
• Vectorwise 2.5 / Linux / 8-Core / 32 Go RAM
• Teradata 6680 with 2 active nodes and SSD (24-core / 192 GB RAM)
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21. Customer Benchmark: Vectorwise VS Teradata
o Result #1:
• Vectorwise was faster than Teradata on all single query runs
o Result #2 :
• Vectorwise was 2x faster than Teradata at 50 queries / minute
o Result #3 :
• With Vectorwise between 1 and 30 queries / minute, queries are running
as fast as in single run
oResult #4:
• At 70 concurrent users (140 queries / minute), Teradata was 100% full
• Vectorwise reach the target of 600 concurrent users (1200 queries /
minute)
• Vectorwise was loaded up to 2000 queries / minute during 2:30 hours
(35% queries were in time out)
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22. Customer Benchmark: Vectorwise VS Teradata
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23. Booster application
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24. Booster application
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25. Booster application
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26. Booster application
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27. Big Data
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28. Iscool Entertainment
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29. Social Gaming
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30. Big Data
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31. Big Data Analysis
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32. Technical architecture
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33. Vectorwise users
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34. Vectorwise users
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35. Conclusion
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36. The Age Of Data
“Data matures like wine, applications like fish.”
- James Governor
Turning Data into Action
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37. Actian Corporation
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38. 70’s
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39. 70’s
1970
1980
1990
1995
MySQL
Ted Codd
Michael Stonebraker
UC Berkeley
Ingres
PostgreSQL








Tandem NonStop SQL
HP Allbase
Cullinet
Britton-Lee
Wang PACE
CA-Universe
Teradata
Informix
Sybase
IBM
System R
MS SQL
Oracle
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40. Actian: 30-year old start up
• +30 years of DBMS experience
UC Berkeley, Relational Technology Inc., Ingres Corporation,
Ask Group, Computer Associates, Ingres Corporation
• Independent since 2006
Ingres became Actian in 2011
• +10 000 customers in 58 countries
• 150 M$ of revenue
• Profitable, +30 M$ of cash
• 500 employees
• 3 acquisitions between December 2012
and April 2014
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41. Disclaimer
This document is for informational purposes only and is subject to change at any
time without notice. The information in this document is proprietary to Actian and
no part of this document may be reproduced, copied, or transmitted in any form or
for any purpose without the express prior written permission of Actian.
This document is not intended to be binding upon Actian to any particular course of
business, pricing, product strategy, and/or development. Actian assumes no
responsibility for errors or omissions in this document. Actian shall have no liability
for damages of any kind including without limitation direct, special, indirect, or
consequential damages that may result from the use of these materials. Actian
does not warrant the accuracy or completeness of the information, text, graphics,
links, or other items contained within this material. This document is provided
without a warranty of any kind, either express or implied, including but not limited to
the implied warranties of merchantability, fitness for a particular purpose, or noninfringement.
Confidential © 2013 Actian Corporation
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