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: