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DB2 10 & InfoSphere Warehouse 10 New Features

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1 DB2 10 & InfoSphere Warehouse 10 New Features

2 Disclaimer The information contained in this presentation is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this presentation, it is provided “as is”, without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this presentation or any other documentation. Nothing contained in this presentation is intended to, or shall have the effect of: Creating any warranty or representation from IBM (or its affiliates or its or their suppliers and/or licensors); or Altering the terms and conditions of the applicable license agreement governing the use of IBM software. Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

3 New Features of DB2 10 and InfoSphere Warehouse 10 DB2 is at the core of both
DB2 10 is the underlying database! DB2 10 DB2 database software offers industry leading performance and reliability on a choice of platform from Linux, Unix and Windows to z/OS InfoSphere Warehouse 10 A complete real-time data warehousing platform that delivers superior scalability and availability, design, build, and management tooling, and business analytics.

4 High Performance. Low Costs.
Ease of Development SQL compatibility, native XML and graph stores, & cloud support Low Operational Cost Parallel processing, deep compression, & automation Reliability High availability, fast recovery, & online utilities Create time-aware tables and queries in less than an hour, not months Protect data privacy with less duplication Designate optimal storage allocation with multi-temperature data management; Compress data dynamically and incrementally with new options Lower costs and risks of creating and maintaining point-in-time queries Based on standard and built for speed “With each release of DB2, I experience faster results with less CPU.” —Martin Hubel, President, Martin Hubel Consulting Inc.

5 Building on the Pillars of DB2
Ease of Development Reliability Low Operational Costs Faster Query Response Improved Index Mgmt Adaptive Compression Multi-Temperature Data Management Real-time Data Warehousing SQL Compatibility enhancements Graph Store Row and Column Access Control Temporal Capabilities DB2 pureScale enhancements Workload Management Enhancements HADR Supports Multiple Standby Servers Create time-aware tables and queries in less than an hour, not months Protect data privacy with less duplication Designate optimal storage allocation with multi-temperature data management; Compress data dynamically and incrementally with new options Lower costs and risks of creating and maintaining point-in-time queries Based on standard and built for speed 5

6 New Release Highlights
Faster business decisions Multiple instances of at least 3x faster performance for complex query workloads 1 Real-time operational data warehousing Lower storage costs Have seen more than one client achieve greater than 7x overall space savings with Adaptive Compression, with some tables achieving more than 10x space savings 2 Multi-Temperature Data Management Improved data availability with DB2 pureScale enhancements Easy switch from Oracle Database to DB2 Average PL/SQL compatibility moves above 98% 3 Based on internal tests of IBM DB2 9.7 FP3 vs. DB with new compression features on P6-550 systems with comparable specifications using data warehouse / decision support workloads, as of 29 Mar 2012. Based on client testing in the DB2 10 Early Access Program. Based on internal tests and reported client experience from 28 Sep 2011 to 07 Mar 2012.

7 Multiple Instances of at least 3x Faster Query Performance
Multiple Instances of at least 3x Faster Query Performance* Increase Ability to Meet SLAs; Postpone Hardware Upgrades Multi-core parallelism enhancements Performance improvements for: Queries over star schemas Queries with joins and sorts Queries with aggregation Hash joins Higher performance Up to 35% faster out-of-the-box performance Multiple instances of at least 3x faster when using new features * Lower costs Postpone hardware upgrades “IBM and Intel® have collaborated over a decade to optimize DB2 performance with Intel® Parallel Studio 2011, software development suite on Intel® Xeon® processors. We are excited to see a ~10x improvement in query processing performance using DB2 10 over the previous DB2 version, running on IBM System x3850 using Intel® Xeon® Processor E7. Customers can now realize dramatically greater performance boost at lower cost per query running IBM DB2 10 on servers powered by Intel® Xeon® processors.” —Pauline Nist, GM Software Strategies, Intel’s Datacenter & Connected Systems Group * Based on both external tests by partners, as well as internal tests of IBM DB2 9.7 FP3 vs. DB with new compression features on P6-550 systems with comparable specifications using data warehouse / decision support workloads, as of 29 Mar 2012.

8 Index Management Re-defined Increase Ability to Meet SLAs; Lower Administration Costs
Jump Scan Smart Index Pre-fetching Smart Data Pre-fetching Predicate Evaluation Avoidance Higher performance Faster index performance Lower costs Fewer indexes to maintain Dramatic reduction in index reorgs Jump Scan – skip sequential Improve performance of indexes with gaps in column definitions Reduced number of indexes Smart Index Pre-fetching Improve performance of index scans for poorly organized indexes Reduced need for index reorgs Smart Data Pre-fetching Improve performance of index scan for + data fetch for poorly clustered tables Reduced need for table reorgs Predicate evaluation avoidance for duplicate keys Improve performance of index scans with duplicate keys “Jump Scan optimizes buffer usage by 75 to 80%, resulting in very good improvement in overall performance and saving the CPU cycles.” —Shanmukhaiah D, Cognizant Technology Solutions.

9 DB2 Workload Management Increase Ability to Meet SLAs; Postpone Hardware Upgrades
CPU limits % of resources DB2 can consume CPU shares % of limit a service class can consume Hard shares and soft shares Available for all platforms Higher performance Prioritize important workloads More efficient distribution of workloads Lower cost Postpone hardware upgrades Other Processes Service Class A Service Class B Service Class C 30% 20% 50% DB2 To begin we must define some of the terms to be used: Dispatch concurrency level: This is the number of threads the WLM dispatcher is allowed to dispatch to the OS concurrently. It is usually recommended to be set at 4* the number of CPUs. It is controlled via a parameter in the DBM cfg, discussed in a later slide. 2) Soft CPU Shares This is the maximum number of shares allocated to a service class while competing service classes use all of their allocated resources. The behaviour of this will be demonstrated in subsequent slides. 3) Hard CPU shares This is the maixmum number of shares allocated to a service class regardless if competing service classes use all of their allocated resources. 4) CPU limit This is the percentage of absolute system CPU resources that DB2 can consume. This will be demonstrated later on to show how this can work for WLM. “The new Workload Manager feature helped us significantly improve performance in our production systems. This makes DB2 an even better alternative for customers who are using other database software." —Elvis Hsu, Technical Supervisor, STI

10 DB2 10 Adaptive Compression DB2 9.7 Temp Space & Index Compression
Breakthrough Savings with Adaptive Compression Lower Storage Costs; Lower Administration Costs DB2 10 Adaptive Compression DB2 9.7 Temp Space & Index Compression DB2 9.1 Table Compression Adaptive Compression is included only in the Storage Optimization feature, and as such is only available for: - Enterprise Server Edition and - Advanced Enterprise Server Edition Significant enhancements to DB2's industry leading compression technologies come in the new Adaptive Compression which can further reduce your storage needs. The enhancements deliver efficient compression of high amounts of new and changing data. The improved compression ratio further reduces storage needs and allows for more data in memory therefore increasing performance. The new approach used in Adaptive Compression also reduces the need for table reorganization. As a consequence, overall maintenance of compressed data is reduced, providing additional cost savings. - New archive log compression reduces log archive storage - Simply turn it on and DB2 does the compression for you - Large SAP customer generates 60GB of log per day and they keep 8 weeks of archives. Storing 3.3TB of archived log files. Compression of 4x results in storage of only 825GB for 8 weeks. Adaptively apply both table-level compression and page-level compression Table re-orgs not required to maintain high compression Compress archive logs

11 Adaptive Compression has provided 7x or greater overall space savings for more than one client, with some tables achieving 10x space savings* 10x 10x 10x 8x 4x 4x Real customer data from beta client shows that DB2 10 Adaptive Compression saves big. This graph represents the largest 5 tables in their database. With DB2 9.7 they were getting between 3X and 6X compression. Using the new adaptive compression in DB2 10 they are now getting between 4X and 10X compression. Note that it was actually their largest table that had the highest savings. For their largest table with 1.5 billion rows they are seeing 10X compression with DB2 10. When we look at their overall table savings, they were seeing 5X compression overall with DB2 9.7 (the last bar on the right). Now with DB2 10 that has increased to 7X compression overall. * Based on client testing in the DB2 10 Early Access Program.

12 Adaptive Compression Shrinks your Data Storage Needs
Higher performance Faster queries for I/O-bound environments Faster backups Lower costs Postpone upcoming storage purchases Lower ongoing storage needs Easier administration with reduced need for table re-orgs “Page-level dynamic compression is one of the new DB2 features that will reduce planned outages and increase storage savings by up to 2X over DB2 9.7%.” —Jessica Tatiana Flores Montiel, DAFROS Multiservicios DB2 Galileo compression is far superior to Oracle for a number of reasons: In order to get the maximum compression possible a customer will need to buy Exadata and use columnar compression The standard compression in Oracle only uses page-level compression so this is not as efficient as using Table and Page level compression Data must be pre-sorted to get the best possible compression ratio – this is often not possible in a production database! Exadata requires the use of “classic” compression if the workloads that are running need to do updates, inserts, and deletes. “Our migration from Oracle Database to DB2 resulted in a 40% storage savings. Upgrading to DB2 9.7 and index compression brought our average savings to 57%. Now adaptive compression brings our average savings to 77%, dramatic savings!” —Andrew Juarez, Lead SAP Basis / DBA, Coca Cola Bottling Company.

13 ARCHIVE Optim Data Growth
Multi-Temperature Data Management Increase Ability to Meet SLAs; Postpone Hardware Upgrades Storage pools for different tiers of storage For range partitions, policy-based automated movement of data Higher performance Improved ability to meet SLAs while retaining greater amount of data for analysis Lower costs Embrace new lower-cost storage technology Further reduces the cost for meeting SLAs HOT SSD RAID WARM SAS RAID COLD SATA RAID ARCHIVE Optim Data Growth Multi-Temperature Data Management is included only in: - Enterprise Server Edition and - Advanced Enterprise Server Edition Tiered Storage is also know as Hierarchical Storage Management (HSM) “The multi-temperature database management feature of DB2 V10.1 is great because the hardware world is not just RAM and hard disks. There are many types of storage options with different I/O speeds and prices. This feature allows administrators to make optimal use of these different devices, balancing expensive SSDs with cheaper SATA disks and everything in between. Using SSDs for indexes and logs and a SATA array for the data, we noticed fantastic improvements in I/O speeds, especially for synchronous reads. Additionally, the background movement of data between the storages groups is very fast.” —Thomas Kalb, CEO ITGAIN GmbH

14 Time Travel Query Easily Analyze Historical Trends and Predict Future Demand
Temporal logic & analysis Valid time, transaction time, “AS OF” queries Higher performance Native support for fast performance Lower costs Eliminate need to maintain and update custom temporal implementations Easy to administer (simply turn on for any table) Query data as it: Is now Was at any point in the past Will be at some point in the future Time Travel Query is available in all DB2 editions: - Express-C - Express Edition - Workgroup Server Edition - Enterprise Server Edition - Advanced Enterprise Server Edition We often feel we'd like to travel to the past to see what our data said at a different point in time. How can we do this without changing our applications? The Time Travel Query function allows you to query data as it as at any point in the past, or as it will be at some point in the future. Time Travel Query, based on the SQL 2011 standard, is integrated into the database engine to provide significant performance and manageability advantages. Time Travel Query provides the infrastructure for time-aware analytics to reduce the operational complexity of collecting and analyzing time-based data. “The use of standardized SQL syntax for temporal operations and the integration deep into the database engine, make DB2 a leader in second generation bitemporal data management - Bitemp 2.0!” —Craig Baumunk, Principal at BitemporalData.com

15 Graph Store Rapid development; Increase Ability to Respond to Emerging Classes of Workloads
Optimized way to store graph triples in DB2 Supports SPARQL 1.0 query language Higher performance Accelerates Rational use case by up to 3.5x* Lower costs Rapid development with schema-less approach Easy adaption as needs evolve Simpler data management for triples Curt Cotner 2012 Ferrari ownsCar 123 Maple Ave, Chicago ownsHouse 2001 Thunderjet ownsBoat Originally developed for Rational Jazz, who were experiencing performance issues with leading open source RDF stores. Offer security, backup/recovery, ACID, compression, load balancing & parallel execution * Based on internal benchmark tests of Rational Jazz graph store usage, comparing DB2 10 Graph Store with Jena TDB version

16 DB2 Graph Store Accelerates Rational Use Case by up to 3.5x*
Faster Query Workload on 60 million triples dataset Jena TDB and DB2 Graph Store run on same machine. Machine runs both server and client. DB2 database size on disk - 30 GB Memory made available - 6 GB Total time across 29 different queries. Read-only workload. (Aside: Also have significant performance advantages for read/write workloads.) Jena TDB runs in-memory. DB2 Graph Store used the “Optimed Graph Store Option” (there are two modes, one of which is “optimized”). In general, the DB2 architecture carries an overhead. This means that the simple queries that execute extremely quickly (1 millisecond or less) will always be slower on DB2. However, with DB2 you also get concurrency, isolation, better scale-out, etc. And when it comes to complex queries, DB2 significantly out-performs Jena TDB. * Based on internal benchmark tests of Rational Jazz graph store usage, comparing DB2 10 Graph Store with Jena TDB version

17 DB2 pureScale Enhancements Increase Ability to Meet SLAs; Easily Add or Remove Capacity
Configurable geographically-dispersed clusters Further Improving IBM’s Shared-Disk Cluster Capability Workload management for DB2 pureScale Multiple database support Easy multi-tenancy Range partitioning support Additional backup/restore options Support for 10-gigabit Ethernet Support for multiple Infiniband adapters and switches - pureScale now supports the DB2 SET WRITE command. The SET WRITE command allows a user to suspend I/O writes or to resume I/O writes for a database. Typical use of this command is for splitting a mirrored database. This type of mirroring is achieved through a disk storage system. - Cluster caching facilities (CFs) now support multiple low-latency, high-speed cluster interconnects. With multiple cluster interconnects on the CFs, you can connect each CF to more than one switch. Adding cluster interconnects, and adding a switch to a DB2 pureScale environment both improve fault tolerance. - With multiple cluster interconnects on the CFs, you can connect each CF to more than one switch. A one-switch multiple cluster interconnect configuration increases the throughput of request to CFs. A two-switch configuration helps with increased throughput and high availability. DB2 pureScale environments do not require multiple cluster interconnects. Can do geographically-dispersed clusters. It’s not a product feature per se. It is not in the official documentation. However, there is a whitepaper on it. This article describes the geographically dispersed DB2® pureScale™ cluster (GDPC). Like the Geographically Dispersed Parallel Sysplex™ configuration of DB2 for z/OS®, GDPC provides the scalability and application transparency of a regular single-site DB2 pureScale cluster, but in a cross-site configuration that enables active/active system availability, even in the face of many types of disasters. The active/active part is important because it means that during normal operation, the DB2 pureScale members at both sites are sharing the workload between them as usual, with workload balancing (WLB) maintaining an optimal level of activity on all members, both within and between sites. This means that the second site is not a standby site, waiting for something to go wrong. Instead, the second site is pulling its weight, returning value for investment even during day-to-day operation. This article describes the prerequisites for a geographically dispersed DB2 pureScale cluster, followed by the steps to one deploy one, as well as some of the performance implications of different site-to-site distances and different workload types. The article covers the following topics: GDPC concepts GDPC infrastructure and prerequisites GDPC setup and configuration Performance factors Detailed configuration steps “Vormetric’s integration with DB2 pureScale GPFS provides IBM customers with a fantastic combination of Vormetric Data Security with pureScale availability, capacity and scalability. Improved performance and availability with data security offers our mutual customers a phenomenal solution.” -- Todd Thiemann, Senior Director, Product Marketing Vormetric, Inc.

18 Row and Column Access Control Easy Compliance with Privacy and Sensitive Data Requirements
Fine-grained access control Hide rows from unauthorized users Mask the value of columns for unauthorized users Policy-driven security, with flexible policies Does not require classification Account Name Income Branch Ana 22,000 A Bob 71,000 B Celia 123,000 Dinesh 172,000 C xxxx-xxxx-xxxx-4444 xxxx-xxxx-xxxx-5555 xxxx-xxxx-xxxx-6666 xxxx-xxxx-xxxx-7777 Teller Amy sees Telemarketer Pat sees Row and Column Access Control is available in all DB2 editions: - Express-C - Express Edition - Workgroup Server Edition - Enterprise Server Edition - Advanced Enterprise Server Edition

19 Easy and Low Cost Security and Privacy Compliance
Higher performance Less data duplication than using “Views” to mask data More secure than using “Views” to mask data Lower cost Easier to implement and maintain Easier compliance with privacy and sensitive data requirements Easier to maintain that using application code to mask data “Because we deal with sensitive securities and financial information, the privacy of that information is a top priority. Row and Column Access Control will help enhance our security solutions and help us meet strict regulatory guidelines.” —Shi Jin Li, China Securities Depository and Clearing Corporation Ltd. “Row and Column Access Control help us to improve data confidentiality and security in production environments.” —Jessica Tatiana Flores Montiel, DAFROS Multiservicios

20 Real-Time Data Warehousing Faster Business Decisions; More Accurate Business Decisions
Continuous feed of data Parallel processing Supports multiple connections Higher performance Faster availability of data Minimal impact on query performance No downtime (even for large volumes of data) Lower costs Costs less than solutions outside database Reduced infrastructure costs Available only in DB2 Advanced Enterprise Server Edition. Easy to administer (powerful scripting capability) Continuous Data Ingest is a specialized utility for continually populating data warehouse tables with minimal impact on concurrent user workload and data server resources. How will it help you Feeds data continuously into your warehouse No downtime needed even for large amounts of data Minimal impact on your current query workload How to start using it Choose a suitable table (new or existing) Define an ingest command with the desired parameters Devise a means to run this command each time there is new data to process (applies to source data in files) “You can now continuously feed data into your data warehouse at a high rate even whilst you are running queries against the tables in your data warehouse. InfoSphere Warehouse 10 represents a greatly strengthened offering for the data warehouse market.” —Ivo Grodtke, LIS.TEC GmbH

21 In DB2 10 Early Access Program testing, DB2 obtained an average of 98% compatibility* with Oracle PL/SQL Easily Move from the More Expensive Oracle Database; Leverage Oracle Skills with DB2 9.7.1 SUB STRB Increase compatibility UDF Parameters: INOUT FORALL/BULK COLLECT Improve BOOLEAN Conditional Compilation Enhancement Basic DPF Support Broaden coverage OCI Support 9.7.2 UDF Parameters: DEFAULT Obfuscation NCHAR, NVARCHAR, NCLOB 9.7.3 NUMBER Performance Performance Runtime “purity level” Enforcement RATIO_TO_REPORT Function RAISE_APPLICATION_ERROR Small LOB Compare 9.7.4 Multi-action Trigger & Update Before Trigger Autonomous Tx Improvements LIKE Improvements, LISTAGG ROW & ARRAY of ROW JDBC Support 9.7.5 Pro*C Support Nested Complex Objects 10 Local Procedure Definitions Local Type Definitions PL/SQL Performance Reliance Life Insurance “The total cost of ownership with DB2 running on IBM systems is almost half the cost of Oracle Database on Sun systems.” Banco de Crédito del Peru “We switched from Oracle Database to IBM DB2 and cut our costs in half, while improving performance and reliability of business applications.” JSC Rietumu Banka • Moved from Oracle Database to IBM DB2 • Used “compatibility features” • 3-30x faster query performance • 200% improvement in data availability In DB2 10 Early Access Program testing, DB2 obtained an average of 98% compatibility with Oracle PL/SQL * Based on internal tests and reported client experience from 28 Sep 2011 to 07 Mar 2012.

22 HADR now Supports Multiple Standby Servers Increase Ability to Meet SLAs; Disaster Recovery
HADR now supports more than one stand-by server If Primary Server fails, Principal Standby takes over If Principal Standby then fails, can switch to Auxiliary Standby Auxiliary Standby can provide complete offsite availability, while maintaining speed of local standby The high availability disaster recover (HADR) feature supports multiple standby databases. This allows you to have your data in more than two sites, providing improved data protection with a single technology. When you deploy the HADR feature in multiple standby mode, you can have up to three standby databases in your setup. You designate one of these databases as the principal HADR standby and any other standby database is an auxiliary HADR standby. Both types of HADR standby are synchronized with the HADR primary through a direct TCP/IP connection, both types support reads on standby, and both types can be configured for time-delayed log replay. In addition, you can issue a forced or non-forced take over on any standby. There are a few important distinctions between the principal and auxiliary standbys, however: IBM® Tivoli® System Automation for Multiplatforms (TSA) automated failover is only supported for the principal standby; you must issue a takeover on one of the auxiliary standbys to make one of them the primary.All of the HADR sync modes are supported on the principal standby only; the auxiliary standbys run in SUPERASYNC mode.

23 Accelerate Value for New Features Increase Ability to Meet SLAs; Lower Administration Costs
Updated Database Admin solutions: IBM Data Studio InfoSphere Data Architect Updated Performance Mgmt solutions: InfoSphere Optim Performance Manager InfoSphere Optim Query Workload Tuner InfoSphere Optim Configuration Manager Higher performance Immediate support for new performance features Enhanced Visual Explain, Access Plan Explorer and Index Advice Extended Insight identifies source of performance issues Lower costs Immediate support for new time saving features (incl. Temporal, Multi-Temperature Data Management & Row and Column Access Control) IBM solutions are integrated and consistent Data Studio Administration of Adaptive Compression Create and alter table, index for adaptive compression Provide compression actions Update Row Compression action in control flow for new options Implementation, Deployment and Maintenance of Storage Groups Create, alter, drop storage groups Create, alter, drop tablespaces within storage groups Generate DDL script from physical database Generate DDL script from compare and synch Compare and synch to validate consistent deployment Analyze impacted objects Implementation, Deployment and Query Analysis of Temporal tables Create, alter, drop tables with temporal attributes Generate Delta DDL script from compare and synch Deploy script to multiple servers using deployment manager Implementation, Deployment and Query Analysis of Row and Column access control Create, alter, drop permissions and masks for users, groups, and roles Create or promote secure functions or secure triggers Activate and deactivate Row and Column access control Analyze impacted objects (e.g. objects needing rebind, made secure) Support for developing Java, C, and .NET applications against a DB2 pureScale environment Perform common administration tasks across DB2 pureScale members and CF Support for high speed unload utility Enhanced Visual Explain, Access Plan Explorer and Index advice to include jump scan and joins Optim Configuration Manager Recommendation compression savings opportunities for tables, indexes and XML objects View compression savings for all objects in the database Policy management Optim Performance Manager Storage group to tablespace alerts Storage group report with drill down to tablespace Route and remap based on data tags Integrated alerting and notification of DB2 pureScale members Seamless view of status and statistics across all DB2 pureScale members and CFs Optim Query Workload Tuner Query, Statistics, and Tuning advice for applications on DB2 pureScale systems InfoSphere Data Architect Logical modeling: system-period, business-period, or bi-temporal Transformation from Logical Modeling to Physical Modeling Physical modeling: system-period, business-period, or bi-temporal Reverse engineering from database and DDL to physical model

24 Coca Cola Bottling Company
“We’ve saved more than a million dollars over the past four years in licensing, maintenance and storage costs by migrating from Oracle Database to DB2. We’ve reinvested these savings into other business projects while keeping our operating expenses flat. As a result, we don’t have to pass rising costs on to consumers, which allow us to maintain our sales volumes and market share.” —Tom DeJuneas, IT Infrastructure Manager, Coca Cola Bottling Company. The need (405 characters/spaces or less; paragraph form using complete sentences) In 2007, rising sugar and gas prices increased the cost to manufacture and deliver beverage products. CCBCC sought to reduce operational costs so it could maintain profitability without raising prices. The company’s IT team had just begun to upgrade its SAP application, which required it to upgrade its Oracle Database. The solution: CCBCC migrated from Oracle Database to IBM DB2 to substantially reduce licensing, maintenance and storage costs and improve database performance. In its continuing quest to improve operational efficiency, CCBCC participated in the IBM DB2 10 best test program and plans to upgrade to the new version for continued savings. The benefit: (3 bullets; not to exceed 125 characters/spaces per bullet) Approximately USD1 million in savings Up to 90 percent faster performance More than 40 percent reduction in database size with an additional 20 percent reduction expected with DB2 10

25 DB2 vs InfoSphere Warehouse At a glance features…
OLTP OLAP/Warehousing DB2 Database Adaptive Compression Multi-Temperature Data Management Time Travel Query Row & Column Access Control DB2 pureScale Continuous Ingest / Real-Time Data Warehousing HADR In addition to above features, InfoSphere Warehouse 10 also includes data mining, cubing and more warehousing tools

26 New Releases Build on the Pillars of DB2
Ease of Development Reliability Low Operational Costs Faster Query Response Improved Index Mgmt Adaptive Compression Multi-Temperature Data Management Real-time Data Warehousing SQL Compatibility enhancements Graph Store Row and Column Access Control Temporal Capabilities DB2 pureScale enhancements Workload Management Enhancements HADR Supports Multiple Standby Servers Create time-aware tables and queries in less than an hour, not months Protect data privacy with less duplication Designate optimal storage allocation with multi-temperature data management; Compress data dynamically and incrementally with new options Lower costs and risks of creating and maintaining point-in-time queries Based on standard and built for speed 26

27 More information Contact us:
IBM India Information Management page (contact information top right) Call IBM India toll free: The New IBM DB2 10: Analyzing Its User Value in Performance, Costs, Ease of Extension, and Risk Management DB2 10 for Linux, UNIX and Windows Web page IBM developerWorks India page for Information Management developerWorks India Information Management Feed contains new DB2 10 articles Information Management evaluation software Break Free from Impractical and Costly IT Solutions brochure DB2 Tech Talk: Technical Tour of DB2 10 and InfoSphere Warehouse 10 Speakers from IBM product labs April 26, 2012, 12:30 PM ET Register:


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