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
