This program provides scalable database server to handle the demanding workloads of large and midsize enterprise servers. It helps you reduce development costs associated with temporal data management. It minimizes the impact of planned and unplanned outages.
v10.5 [Jun 20, 2014]
- In-memory optimization for maximal performance. Compressed column-organized data can be stored very efficiently, which reduces the amount of memory that is needed for (and increases the speed of) query processing. With an in-memory optimized database, all of the data can be loaded into memory, and performance bottlenecks can be avoided.
- A system that is unconstrained by main memory size, in which the data being processed can be considerably larger than the RAM.
- Improved system scaling across cores.
- An enhanced caching strategy for buffer pools to substantially reduce I/O costs.
- A smaller footprint for database storage than DB2 10.
- Late decompression, the ability to operate directly on compressed data for certain operations, thereby reducing memory usage.
- Multiplied CPU power that uses single instruction, multiple data (SIMD) processing for many operations.
Vector processing of several column data values at once, instead of individual values.
Feature-rich relational database known for its high performance and excellent concurrency
