Application development in partitioned databases

Database partitioning works on the divide and conquer rule. When the data grows, we can use different partitioning techniques to divide the data into smaller chunks, and then process it, resulting in very good performance. Typically, we come across large data volumes in business intelligence environments where we perform deep analysis on historical data. A typical installation of a data warehouse involves more than one partitioning technique. When we are designing applications for large databases that are partitioned, we need to make sure that our applications are also designed in a way that they can get benefit from the underlying partitioned database. In this recipe, we will discuss the different partitioning techniques that DB2 provides, and what should be considered for designing applications in such an environment.

How to do it

DB2 provides three main techniques for partitioning:

• Database partitioning

• Range partitioning

• Multidimensional...