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MySQL Cluster, also known as MySQL Ndb Cluster is a technology providing shared-nothing clustering and auto-sharding for the MySQL database management system. It is designed to provide high availability and high throughput with low latency, while allowing for near linear scalability. [ 3 ]
The server is a transforming proxy (e.g. a Web accelerator) that received a 200 OK from its origin, but is returning a modified version of the origin's response. [1]: §15.3.4 [1]: §7.7 204 No Content The server successfully processed the request, and is not returning any content. 205 Reset Content
MariaDB is intended to maintain high compatibility with MySQL, with exact matching with MySQL APIs and commands, allowing it in many cases to function as a drop-in replacement for MySQL. However, new features are diverging. [7] It includes new storage engines like Aria, ColumnStore, and MyRocks.
MySQL (/ ˌ m aɪ ˌ ɛ s ˌ k juː ˈ ɛ l /) [6] is an open-source relational database management system (RDBMS). [6] [7] Its name is a combination of "My", the name of co-founder Michael Widenius's daughter My, [1] and "SQL", the acronym for Structured Query Language.
MySQL Workbench 5.0 and 5.1 are specialized visual database design tools for the MySQL database. While MySQL Workbench 5.0 was a MS Windows-only product, cross-platform support was added to MySQL Workbench 5.1 and later. [14] [15]
In computer programming, create, read, update, and delete (CRUD) are the four basic operations (actions) of persistent storage. [1] CRUD is also sometimes used to describe user interface conventions that facilitate viewing, searching, and changing information using computer-based forms and reports.
Codd's twelve rules [1] are a set of thirteen rules (numbered zero to twelve) proposed by Edgar F. Codd, a pioneer of the relational model for databases, designed to define what is required from a database management system in order for it to be considered relational, i.e., a relational database management system (RDBMS).
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]