Because of business needs for data retention and regulatory compliance,
enterprises need to manage increasingly large databases ranging from
hundreds of gigabytes to many terabytes, or even petabytes, in size. As
data continues to grow at an exponential rate, DBAs and IT professionals
in these organizations face daunting challenges when designing and
operating such large databases. The data must be well organized to
effectively cope with data growth and to meet service requirements.
Challenges include how best to achieve the following objectives.
- Designing databases that can accommodate continuous data growth.
- Keeping database systems lean and high performing.
- Managing data lifecycles more efficiently and less intrusively to keep
operational data highly available.
- Reducing the cost and impact of data maintenance operations, such as
backup and restore operations, to keep mission-critical data ready
when needed, and reorganization and runstats operations to maximize
- Satisfying near real-time requests for transactional data or the
complex analytical query requirements for large data sets, often
including historical data, while reducing the total cost of ownership
DB2 for Linux, UNIX, and Windows offers a rich set of features that help
you to meet these challenges and to benefit from winning solutions. This
paper describes best practices for managing data growth that you can
consider during the stages of database planning, design, implementation,
and operation. By leveraging these best practices, DBAs and IT
professionals can use DB2 data server’s extensible architecture and the
layered data partitioning and organization schemes to take full advantage
of proven approaches to managing data growth.
Read the entire best practices paper found here on deloperworks: http://www.ibm.com/developerworks/data/bestpractices/managingdatagrowth/index.html