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MEMORY is a storage engine for MySQL and MariaDB relational database management systems, developed by Oracle and MariaDB. Before the version 4.1 of MySQL it was called Heap. The SHOW ENGINES command describes MEMORY as: Hash based, stored in memory, useful for temporary tables. MEMORY writes table data in-memory.
This is a comparison between notable database engines for the MySQL database management system (DBMS). A database engine (or "storage engine") is the underlying software component that a DBMS uses to create, read, update and delete (CRUD) data from a database .
Note (1): Firebird 2.x maximum database size is effectively unlimited with the largest known database size >980 GB. [79] Firebird 1.5.x maximum database size: 32 TB. Note (2): Limit is 10 38 using DECIMAL datatype. [80] Note (3): InnoDB is limited to 8,000 bytes (excluding VARBINARY, VARCHAR, BLOB, or TEXT columns). [81]
MySQL (/ ˌ m aɪ ˌ ɛ s ˌ k juː ˈ ɛ l /) [5] is an open-source relational database management system (RDBMS). [5] [6] Its name is a combination of "My", the name of co-founder Michael Widenius's daughter My, [7] and "SQL", the acronym for Structured Query Language.
InnoDB is a storage engine for the database management system MySQL and MariaDB. [1] Since the release of MySQL 5.5.5 in 2010, it replaced MyISAM as MySQL's default table type. [2] [3] It provides the standard ACID-compliant transaction features, along with foreign key support (declarative referential integrity).
HeidiSQL is a free and open-source administration tool for MariaDB, MySQL, as well as Microsoft SQL Server, PostgreSQL and SQLite. Its codebase was originally taken from Ansgar Becker's own MySQL-Front 2.5 software. After selling the MySQL-Front branding to an unrelated party, Becker chose "HeidiSQL" as a replacement.
Varchar fields can be of any size up to a limit, which varies by databases: an Oracle 11g database has a limit of 4000 bytes, [1] a MySQL 5.7 database has a limit of 65,535 bytes (for the entire row) [2] and Microsoft SQL Server 2008 has a limit of 8000 bytes (unless varchar(max) is used, which has a maximum storage capacity of 2 gigabytes).
Should an increase in database size cause the number of accessors of the database to increase then more server and network resources may be consumed, and the risk of contention will increase. Some solutions to regaining performance include partitioning, clustering, possibly with sharding, or use of a database machine. [23]: 390 [24]