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What’s new for analytics in DB2 10.5 “Cancun Release”

Amit Patel, Data Warehousing Expert

A blog post by Amit Patel, IBM Program Director, Data Warehousing solutions

 

DB2 10.5 “Cancun Release” is now available. Let’s discuss what’s new in this release and why clients should take advantage of the new and powerful enhancements to BLU Acceleration.

 

BLU Shadow Tables enable in the moment transaction reporting

Arguably the most notable feature of this release is the ability to take advantage of BLU Acceleration directly in transaction processing systems with BLU Shadow Tables. Typically, data is replicated from various sources like transaction processing systems, and integrated to a separate data warehouse or data mart for running analytic queries. However, with the increasing focus on driving insights in real-time from operational data, there is a business need to run reporting and analytics in some cases directly in the transaction processing system. The DB2 10.5 “Cancun Release” enables clients to simplify their IT landscape with reporting and transactions in one DB2 system.

Shadow Tables, powered by BLU Acceleration, automatically maintain in the transaction processing environment a column-based version of the row-based operational data. DB2 query optimizer seamlessly routes analytic queries to BLU Shadow Tables that are optimized for analytic workloads. This means clients can get the answers they need in the moment, directly from the transaction processing system, without having to replicate and integrate the operational data into a separate data mart or data warehouse. DB2 now gives clients greater choices and control over their IT landscape by opening new possibilities for accelerating reporting and analytics and simplifying their infrastructure.

Oracle SQL compatibility for low risk migration from Oracle to BLU Acceleration

With the DB2 “Cancun Release”, BLU Acceleration offers SQL compatibility for simple, low-risk migration from Oracle database to DB2 with BLU Acceleration. This means clients can leverage their existing Oracle database skills and investments while taking advantage of the speed and simplicity of BLU Acceleration.

Significant enhancements to SAP BW support

DB2 “Cancun Release” offers significant enhancements to SAP BW Support. BLU Acceleration now supports a much broader and comprehensive range of SAP BW objects. Major enhancements have been made to insert, update, delete, and data integration. IBM and SAP have a 15-year history of engineering partnership to deliver improved solutions to mutual clients. DB2 allows SAP clients to maintain investments in existing environments and skills, and adopt next-generation in-memory computing without disrupting their business.

First database optimized for the POWER8 processor

This release makes DB2 the world’s first database optimized for POWER8 processor. With BLU Acceleration and the POWER8 hardware, we observed an average performance improvement of 82x on report generation compared to a competitor running on x86 platform.*

DB2 offers optimizations to take full advantage of superior concurrent multithreading capabilities of POWER8 processors. With its CPU Acceleration capabilities, DB2 can utilize the 128-bit register instructions in POWER8 processors for faster query processing. Improvements in Data Page Memory Checking and increased use of integrity checking deliver better reliability to clients.

DB2 with BLU Acceleration became available in June of 2013, and just over a year later, it’s even better with the DB2 “Cancun Release”. If you like what you have read so far,  take DB2 with BLU Acceleration for a test drive here.

Read Amit’s additional blog posts on in-memory computing and BLU Acceleration.

 Footnote

* Based on IBM internal tests as of April 7, 2014 comparing IBM DB2 with BLU Acceleration on Power with a comparably tuned competitor row store database server on x86 executing a materially identical 2.6TB BI workload in a controlled laboratory environment. Test measured 60 concurrent user report throughput executing identical Cognos report workloads. Competitor configuration: HP DL380p, 24 cores, 256GB RAM, Competitor row-store database, SuSE Linux 11SP3 (Database) and HP DL380p, 16 cores, 384GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). IBM configuration: IBM S824, 24 cores, 256GB RAM, DB2 10.5, AIX 7.1 TL2 (Database) and IBM S824, 16 of 20 cores activated, 384GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). Results may not be typical and will vary based on actual workload, configuration, applications, queries and other variables in a production environment.
82x calculation based on geometric mean calculation giving equal weighting to the report per hour (RPH) improvements in the three categories of simple, intermediate, and complex reports. GEOMEAN(RPH_simple,RPH_intermediate,RPH_complex) = GEOMEAN(18.85,40.07,747.63)=82.66

 
 

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