Beautify SQL queries online for easier review and debugging.
TempGBox
SQL Formatter
Format and beautify SQL queries. All processing happens locally in your browser.
What is SQL Formatter?
SQL Formatter helps with SQL Formatter Online. Format and beautify SQL queries. Supports MySQL, PostgreSQL, MSSQL, Oracle, and standard SQL.
TempGBox keeps the workflow simple in your browser, so you can move from input to result quickly without extra software.
How to use SQL Formatter
- Open SQL Formatter and enter the text, value, file, or settings you want to work with.
- Review the output and adjust the available options until the result matches your use case.
- Copy, download, or reuse the final result in your workflow, content, app, or support task.
Why use TempGBox SQL Formatter?
- Format and beautify SQL queries. Supports MySQL, PostgreSQL, MSSQL, Oracle, and standard SQL
- Useful for SQL Formatter Online
- Fast browser-based workflow with no signup required
Common uses for SQL Formatter
SQL Formatter is useful for SQL Formatter Online. It fits well into quick checks, repeated office work, development flows, content updates, and everyday browser-based problem solving.
Because the tool is available instantly on TempGBox, you can handle one-off tasks and repeated workflows without installing extra software.
FAQ
Is SQL Formatter free to use?
Yes. SQL Formatter on TempGBox is free to use and does not require signup before you start.
What is SQL Formatter useful for?
SQL Formatter is especially useful for SQL Formatter Online.
Understanding SQL Formatter
SQL formatting conventions have never been formally standardized, but strong community consensus has emerged around a set of practices that improve readability and maintainability. The most widely adopted convention places each major clause (SELECT, FROM, WHERE, JOIN, GROUP BY, ORDER BY, HAVING, LIMIT) on its own line at the leftmost indentation level, with their arguments indented one level further. Column lists in SELECT and conditions in WHERE each get their own line, with leading commas or leading AND/OR operators aligned vertically. This style — sometimes called the "rivers" or "left-aligned keyword" style — makes it immediately clear where each clause begins and how many conditions or columns are involved.
SQL dialects diverge significantly beyond standard DML (SELECT, INSERT, UPDATE, DELETE). MySQL uses backticks for identifier quoting (`table_name`), LIMIT/OFFSET for pagination, and IF() for inline conditionals. PostgreSQL uses double quotes ("table_name"), LIMIT/OFFSET plus the standard FETCH FIRST syntax, and has rich type support including arrays, JSONB, and range types. SQLite has minimal type enforcement (all values are stored as one of NULL, INTEGER, REAL, TEXT, or BLOB), uses standard double-quote quoting but also accepts backticks for MySQL compatibility, and lacks ALTER TABLE DROP COLUMN (added only in 3.35.0). SQL Server uses square brackets ([table_name]), TOP instead of LIMIT, and has proprietary syntax for window functions, pivots, and CTEs that differ subtly from the ANSI standard.
Common Table Expressions (CTEs, introduced in SQL:1999 and supported by PostgreSQL 8.4+, MySQL 8.0+, SQLite 3.8.3+, SQL Server 2005+) use the WITH clause to define named temporary result sets. CTEs make complex queries readable by decomposing them into logical steps: WITH active_users AS (SELECT ...), recent_orders AS (SELECT ...) SELECT ... FROM active_users JOIN recent_orders. Recursive CTEs (WITH RECURSIVE) enable tree traversal and graph queries — finding all subordinates of a manager, computing bill-of-materials explosions, or generating series without dedicated functions. Formatting CTEs properly — each CTE definition on its own indented block — is critical because unformatted CTEs become unreadable faster than any other SQL construct.
Window functions (OVER clause) perform calculations across rows related to the current row without collapsing the result set like GROUP BY does. ROW_NUMBER(), RANK(), DENSE_RANK(), LEAD(), LAG(), SUM() OVER, and AVG() OVER are the most commonly used window functions. The PARTITION BY clause divides rows into groups (like GROUP BY but without aggregation), and ORDER BY within the window determines the processing order. Frame specifications (ROWS BETWEEN, RANGE BETWEEN) further refine which rows participate in the calculation. Formatting window functions readably means placing the OVER clause on the same line or a new indented line, and breaking complex frame specifications into their own lines.
Step-by-Step Guide
- Paste your SQL query into the input area. The formatter handles single statements and multi-statement scripts separated by semicolons. It recognizes standard SQL, CTEs, subqueries, window functions, and common dialect-specific syntax.
- Select the SQL dialect to apply dialect-specific formatting rules: MySQL, PostgreSQL, SQLite, SQL Server (T-SQL), or Standard SQL. Dialect selection affects identifier quoting style, keyword recognition, and function name casing.
- Choose the keyword case convention: UPPERCASE (SELECT, FROM, WHERE — the most common convention), lowercase, or preserve original. Uppercase keywords provide the strongest visual distinction between SQL syntax and user-defined identifiers.
- Set the indentation width (2 or 4 spaces) and whether to use leading commas (commas at the start of each line, making it easy to comment out columns) or trailing commas (commas at the end, matching natural reading order).
- Click Format to transform the query. The formatter parses the SQL into an AST, applies the formatting rules, and produces consistently indented output with one clause per line and aligned conditions.
- Review the formatted output for logical correctness. Proper formatting often reveals bugs: a WHERE condition that should be in a HAVING clause, a JOIN missing its ON condition, or a subquery with incorrect parenthesization become visible when the structure is properly indented.
- Copy the formatted SQL into your codebase, migration files, or database client. For queries embedded in application code, consider whether the formatted multi-line string or a query builder produces more maintainable results.
Real-World Use Cases
A data analyst receives a 200-character single-line query from a monitoring dashboard and needs to modify the WHERE clause. Formatting it reveals a query with three JOINs, a subquery in the WHERE clause, and a GROUP BY with HAVING — the one-line version was essentially unreadable.
A database administrator optimizing slow queries extracts SQL from the PostgreSQL slow query log, where queries are logged without formatting. Running each through the formatter reveals redundant subqueries, missing indexes (identifiable from formatted WHERE clauses), and opportunities to replace correlated subqueries with JOINs.
A development team adopts a SQL style guide requiring uppercase keywords, leading commas, and 4-space indentation. They use the formatter as a pre-commit hook for .sql files, ensuring every migration file matches the team standard regardless of which developer wrote it.
A junior developer writes a complex CTE query for a report and asks a senior developer for review. The senior developer formats the query first, which reveals that the recursive CTE is missing its termination condition — a bug that would cause an infinite loop at runtime.
Expert Tips
Use the dialect-specific mode when formatting vendor-specific syntax. MySQL's GROUP_CONCAT, PostgreSQL's FILTER (WHERE ...), SQL Server's CROSS APPLY, and SQLite's INSERT OR REPLACE all have unique syntax that a generic SQL formatter may mishandle or fail to recognize.
For queries embedded in application code (e.g., template strings in Python or JavaScript), format the SQL separately and then paste it back. Inline SQL in application code is one of the hardest things to read in a codebase — proper formatting and a tagged template or multi-line string make a significant difference.
When reviewing complex queries, format them with one condition per line in the WHERE clause. This layout makes it easy to verify each condition independently and to spot missing conditions that should be present based on the business logic.
Frequently Asked Questions
Should SQL keywords be uppercase or lowercase?
This is a style preference, not a functional requirement — SQL keywords are case-insensitive. Uppercase (SELECT, FROM, WHERE) is the most widely adopted convention because it creates clear visual separation between SQL syntax and user-defined names like table and column identifiers. Some modern teams prefer lowercase for readability in code editors with syntax highlighting.
What are leading commas and why do some teams prefer them?
Leading commas place the comma at the beginning of each line rather than the end: ", column_name" instead of "column_name,". This makes it trivial to comment out any column by adding -- at the start of the line without worrying about trailing comma syntax errors. It also makes diffs cleaner when adding or removing columns.
How should CTEs be formatted?
Place the WITH keyword on its own line, indent each CTE definition, and separate multiple CTEs with a comma on its own line. The CTE name and AS keyword go on one line, the opening parenthesis on the same line or next, the CTE body indented, and the closing parenthesis aligned with the CTE name. This structure makes each CTE's boundaries and purpose immediately clear.
Does formatting affect SQL performance?
No. Whitespace and line breaks are stripped during SQL parsing. A minified single-line query and a beautifully formatted multi-line query produce identical execution plans. Formatting is purely for human readability and maintainability — the database engine never sees your indentation.
How should window functions be formatted?
Keep simple window functions on one line: ROW_NUMBER() OVER (PARTITION BY dept ORDER BY salary DESC). For complex frame specifications, break the OVER clause onto indented lines: OVER (\n PARTITION BY dept\n ORDER BY salary\n ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING\n). This prevents long lines and makes the partitioning, ordering, and frame logic individually readable.
Privacy: SQL formatting is performed entirely in your browser. Your queries — including table names, column names, conditions, and any data literals — are never transmitted to any server or logged.