1.SQL and storage engine

1. Introduction to
SQL SQL is the abbreviation of Structured Query Language, that is, structured query language. SQL is a standard computer language used to access and operate databases. Its main functions include data control, data definition, data manipulation and data query.

2. SQL function
Data Definition Language DDL (Data Definition Language): used for adding, deleting and modifying databases, data tables, views, etc. DDL includes create, alter, and drop commands.
Data manipulation language DML (Data Manipulation Language): used to add, delete and modify records in the data table. DML includes insert, delete and update commands.
Data query language DQL (Data Query Language): used to query records in the data table. DQL uses the select command.
Data Control Language DCL (Data Control Language): Used for authority management and transaction management of database objects. DCL includes commit, rollback, and grant commands.

3. Introduction to
storage engine The storage engine is the underlying software organization of the database. The database management system (DBMS) uses the data engine to add, delete, modify and query data. Different storage engines provide different storage mechanisms, indexing techniques, and locking levels. Using different storage engines can also obtain specific functions.

4. View storage engines supported by MySQL

show engines;

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Storage engine Storage engine
InnoDB Support ACID transactions, row-level locks, foreign keys, etc.; MySQL 5.5 or later, the default storage engine used
MyISAM Has faster insertion and query speed, but does not support transactions; versions before MySQL 5.5, use the default storage engine
MRG_MYISAM Aggregate a group of MyISAM tables with the same structure into a whole, and then perform addition, deletion, modification, and check operations
MEMORY All data is stored in memory, and the response is fast; all data will be lost when MySQL restarts
ARCHIVE Archiving and compression mechanism, suitable for historical data archiving
CSV Logically separate data by commas, and create a .csv file for each table

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