Reading and writing database pages from and to disk is the slowest aspect of system performance. Therefore, compression attempts to reduce I/O by using CPU time to compress and uncompress data, and thus is most effective when I/O is a relatively scarce resource compared to processor cycles.

This is often especially the case when running in a multi-user environment with fast, multi-core CPUs. When a page of a compressed table is in memory, InnoDB often uses an additional 16K in the buffer pool for an uncompressed copy of the page. The adaptive LRU algorithm in the InnoDB storage engine attempts to balance the use of memory between compressed and uncompressed pages to take into account whether the workload is running in an I/O-bound or CPU-bound manner. Nevertheless, a configuration with more memory dedicated to the InnoDB buffer pool tends to run better when using compressed tables than a configuration where memory is highly constrained.