MEMORY performance is constrained by contention resulting from single-thread execution and table
lock overhead when processing updates. This limits scalability when load increases, particularly for
statement mixes that include writes.
Despite the in-memory processing for MEMORY tables, they are not necessarily faster than InnoDB
tables on a busy server, for general-purpose queries, or under a read/write workload. In particular, the
table locking involved with performing updates can slow down concurrent usage of MEMORY tables from
Depending on the kinds of queries performed on a MEMORY table, you might create indexes as either
the default hash data structure (for looking up single values based on a unique key), or a generalpurpose
B-tree data structure (for all kinds of queries involving equality, inequality, or range operators
such as less than or greater than). The following sections illustrate the syntax for creating both kinds
of indexes. A common performance issue is using the default hash indexes in workloads where B-tree
indexes are more efficient.
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