Over the years, processors and cache memories have become much faster, but mass storage based on rotating magnetic disks has not kept pace. While the storage capacity of disks has grown by about a factor of 1,000 in the past decade, random seek times and data transfer rates are still severely limited by mechanical constraints. Therefore, many workloads are I/O-bound. The idea of data compression is to pay a small cost in increased CPU utilization for the benefit of smaller databases and reduced I/O to improve throughput, potentially significantly.

The ability to compress user data is an important new capability of the InnoDB storage engine. Compressed tables reduce the size of the database on disk, resulting in fewer reads and writes needed to access the user data. For many InnoDB workloads and many typical user tables (especially with read-intensive applications where sufficient memory is available to keep frequently-used data in memory), compression not only significantly reduces the storage required for the database, but also improves throughput by reducing the I/O workload, at a modest cost in processing overhead. The storage cost savings can be important, but the reduction in I/O costs can be even more valuable.