Data
SQL Formatter & Query Beautifier
Beautify complex, messy, or minified SQL queries into clean, standardized statements with customized indentation and keyword capitalization. Supports PostgreSQL, MySQL, SQLite, and MariaDB syntax with client-side tokenization and single-line minification.
How it works
The SQL formatter operates via a lexical tokenizer that parses string literals (preserving single quotes, double quotes, and backticks), single-line comments (--), block comments (/* ... */), and SQL keywords. It structures major relational clauses (SELECT, FROM, WHERE, JOIN, GROUP BY, HAVING, ORDER BY, LIMIT) onto new indentation blocks. Sub-clauses such as AND and OR are indented under their parent conditionals, while parenthesized subqueries increment indentation depth. Minification strips comments and collapses whitespace into a single line suitable for database CLI logs or environment variables.
How to use it
- Paste your raw, minified, or unformatted SQL query into the input editor.
- Select your preferred indentation: 2 spaces, 4 spaces, or tabs.
- Choose keyword casing: UPPERCASE (SELECT, FROM, WHERE), lowercase, or preserve original casing.
- Click 'Format / Beautify' to structure clauses and subqueries, or 'Minify Single-Line' for logs.
- Copy the cleaned SQL query to your clipboard or download it as a .sql file.
Worked Examples
Example 1: Beautifying Multi-Table Join & Aggregation Query
Worked ExampleRefactoring a 300-character single-line SQL query captured from an application APM trace.
Input Payload
select o.id, c.name, sum(i.qty*i.price) as total from orders o inner join customers c on c.id=o.cust_id left join items i on i.order_id=o.id where o.status='completed' group by o.id, c.name order by total desc limit 10;
Output / Result
SELECT o.id, c.name, sum(i.qty * i.price) AS total FROM orders o INNER JOIN customers c ON c.id = o.cust_id LEFT JOIN items i ON i.order_id = o.id WHERE o.status = 'completed' GROUP BY o.id, c.name ORDER BY total DESC LIMIT 10;
Why this happens: Breaks major SQL clauses onto dedicated lines, indents SELECT projections, and aligns JOIN relationships for immediate developer readability.
Example 2: Formatting Common Table Expressions (CTEs)
Worked ExampleStructuring a multi-step analytical window query with WITH clauses.
Input Payload
with active_users as (select user_id, count(*) as login_count from logins where created_at >= '2026-01-01' group by user_id) select * from active_users where login_count > 5;
Output / Result
WITH active_users AS ( SELECT user_id, count(*) AS login_count FROM logins WHERE created_at >= '2026-01-01' GROUP BY user_id ) SELECT * FROM active_users WHERE login_count > 5;
Why this happens: Indents CTE definitions cleanly so engineers can review data transformations before query execution.
Example 3: Minifying SQL for Log Injection and Environment Files
Worked ExampleCollapsing a multi-line migration query into a single line for automated bash execution.
Input Payload
SELECT * FROM users WHERE email = '[email protected]';
Output / Result
SELECT * FROM users WHERE email = '[email protected]';
Why this happens: Removes line feeds and superfluous spaces while strictly preserving literal string contents.
Edge Cases & Failure Modes
SQL Keywords Embedded Inside String Literals
Queries containing values like `WHERE note = 'PLEASE SELECT FROM MENU'` can confuse naive regex formatters into breaking the string literal.
Handling: Our tokenizer treats strings enclosed in single quotes, double quotes, or backticks as atomic tokens, preventing internal keyword replacement.
Multi-Word Clause Identifiers
Keywords like `LEFT OUTER JOIN`, `GROUP BY`, `ORDER BY`, and `UNION ALL` must be treated as single conceptual clauses rather than split across words.
Handling: A forward-looking lexical analyzer recognizes multi-word SQL clauses before individual keyword tokenization.
Database Dialect Differences
PostgreSQL, MySQL, SQLite, and Oracle have varying quoting conventions (e.g. backticks in MySQL vs double quotes in Postgres).
Handling: The formatter respects all three standard identifier quoting styles (backtick, double-quote, single-quote) without altering dialect-specific syntax.
Privacy & Local Execution Guarantee
SQL formatting, clause parsing, and query minification execute completely in your browser memory. Database schemas, table names, SQL queries, and sensitive WHERE parameters never leave your local device.
Frequently Asked Questions
Which database SQL dialects does this tool support?
It formats standard ANSI SQL as well as dialect-specific syntax for PostgreSQL, MySQL, MariaDB, SQLite, Oracle, Microsoft SQL Server, and Amazon Redshift.
Does formatting SQL change how the database executes the query?
No. Relational database query planners (Postgres, MySQL, SQLite) parse SQL into an Abstract Syntax Tree (AST), discarding formatting whitespace. A formatted query executes with identical query execution plans and performance.
Can I format queries that contain SQL comments?
Yes. Both single-line comments (`-- comment`) and multi-line block comments (`/* comment */`) are preserved and aligned with their corresponding query blocks.
What is the difference between uppercase and lowercase SQL keywords?
Most SQL dialects are case-insensitive regarding keywords. However, capitalizing keywords (`SELECT`, `FROM`, `WHERE`) is the universally accepted industry standard because it visually separates SQL commands from column and table names.
Is my SQL query or schema sent to any external server?
No. All parsing and formatting happens 100% locally in your browser memory. Your internal queries, table names, and parameters remain strictly private.
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