SQL Formatter & Beautifier

Format and beautify SQL queries for better readability.

Paste SQL from logs, ORM output, migration files, or database consoles and turn it into a readable query before debugging or sharing it in a pull request. The formatter focuses on structure: clauses, joins, indentation, keyword casing, and compact minified output when you need a single-line query.

Formatting SQL Queries

Complex SQL queries become unreadable when written on one line. This tool adds proper indentation and line breaks - keywords like SELECT, FROM, WHERE, JOIN get their own lines, and nested queries are indented.

Paste your messy query, get back something you can actually understand. Especially useful when debugging queries from logs or explaining code to teammates.

What Gets Formatted

  • Major clauses (SELECT, FROM, WHERE, ORDER BY) on new lines
  • JOINs indented and aligned
  • Subqueries properly nested
  • Consistent keyword capitalization

Safe SQL Formatting Notes

  • Formatting does not validate logic: A prettier query can still have an incorrect join, filter, or aggregation.
  • Review quoted strings: Keep an eye on SQL that contains JSON, escaped quotes, or vendor-specific syntax.
  • Remove secrets first: Redact production credentials, tokens, and customer data before pasting queries from logs.
  • Compare before running: For migrations or destructive statements, diff the formatted SQL against the original before execution.

When Developers Actually Use This

The scenario that brings most developers to a SQL formatter: you're debugging a slow query or a data issue, and you pull the raw SQL from your ORM's query log, an error message, or a monitoring tool. What you get looks like SELECT u.id,u.name,o.total FROM users u LEFT JOIN orders o ON u.id=o.user_id WHERE u.created_at>'2024-01-01' AND o.status='completed' GROUP BY u.id ORDER BY o.total DESC LIMIT 50 — one long string with no line breaks. Understanding the join conditions, checking the WHERE clause logic, or spotting a missing index hint becomes genuinely difficult when you can't visually parse the structure.

Formatted properly, that same query becomes immediately readable — you can see at a glance that it's a LEFT JOIN (not INNER), that the GROUP BY might be causing a performance issue, and that there's no index hint for the date range filter. This is also useful when writing documentation or adding queries to a README — well-formatted SQL is significantly easier for teammates to review in pull requests. Copying raw SQL from a database client and cleaning it up before sharing is a small habit that saves a lot of back-and-forth in code reviews.