Dev / Text & Code / SQL Formatter

MySQL Formatter — Format MySQL Queries Online Free

Format, minify, validate SQL · Auto-detect dialect · AI explain & optimize

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MySQL Formatter formats MySQL queries with full support for MySQL-specific syntax — AUTO_INCREMENT, ENGINE, CHARSET, COLLATE, ENUM, TINYINT, MEDIUMINT, BIGINT, ON DUPLICATE KEY UPDATE, and more. AI explain and optimize your MySQL queries directly in the browser.

or drag & drop .sql / .txt anywhere · max 5MB
Ctrl+M to cycle
Dialect
✦ AI
INPUT
Indent
Keywords
OUTPUT
Formatted SQL will appear here…
In: 0 chars · 0 lines·Out: 0 chars · 0 B·0ms
0 uses · 0 secondsmin saved

About SQL Formatter

MySQL Formatter formats MySQL queries with full support for MySQL-specific syntax — AUTO_INCREMENT, ENGINE, CHARSET, COLLATE, ENUM, TINYINT, MEDIUMINT, BIGINT, ON DUPLICATE KEY UPDATE, and more. AI explain and optimize your MySQL queries directly in the browser.

Frequently Asked Questions

What MySQL-specific keywords are supported?

Supported MySQL keywords include: AUTO_INCREMENT, ENGINE, CHARSET, COLLATE, TINYINT, MEDIUMINT, BIGINT, ENUM, SET, SHOW, DESCRIBE, ON DUPLICATE KEY UPDATE, and MySQL-specific functions like NOW(), DATE_FORMAT(), IFNULL().

Can I format MySQL stored procedures?

The formatter handles standard SQL including BEGIN/END blocks, but full stored procedure formatting with DELIMITER is best done in MySQL Workbench or a dedicated IDE.

Does it support MySQL window functions?

Yes. Window functions like ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), LEAD(), OVER(), PARTITION BY are all recognized and properly formatted — these were added in MySQL 8.0.

What does dialect auto-detect do for MySQL?

When you paste a query, the tool scans for MySQL-specific keywords like AUTO_INCREMENT, ENGINE=InnoDB, or ON DUPLICATE KEY UPDATE and automatically identifies the query as MySQL dialect.

Can AI Optimize help with MySQL query performance?

Yes. AI Optimize specifically considers MySQL optimization strategies — like adding appropriate indexes, replacing correlated subqueries with JOINs, using EXISTS instead of IN for large datasets, and optimizing GROUP BY queries.

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