SQLフォーマッター＆整形ツールエンジニアのための高速ツール
SQLクエリをミリ秒単位で美しく整形、圧縮、リファクタリング。サーバー通信ゼロ、先頭カンマ配置、ビジュアル差分比較、8言語へのコード文字列エクスポートに対応。
Free Online SQL Query Formatter, Beautifier and Minifier Workbench
高速・安全・高精度なSQL整形機能
読みづらい長大なSQLクエリを本番運用に耐えうる美しいコードへと変換します。
100% Client-Side Privacy
Your queries never leave your computer. Formatting runs entirely in your browser's local sandbox with zero server telemetry, making it compliant for healthcare, banking, and confidential database schemas.
20+ SQL Dialects & Cloud Data Warehouses
Standard ANSI, PostgreSQL, MySQL, Snowflake, Google BigQuery, Microsoft T-SQL, Oracle PL/SQL, Redshift, Spark, SQLite, and ClickHouse. Paste your query and our engine automatically identifies the dialect.
Visual Diff & Review Mode
Verify safety before committing. Switch directly into visual diff mode to see exact line-by-line additions, deletions, and whitespace modifications between raw code and beautified output.
Leading Comma Style
The beloved "Comma-First" style used by data engineers and enterprise DBAs. Placing commas at the start of column lines prevents missing comma errors and produces pristine 1-line Git diffs when adding columns.
Smart Paste Auto-Cleaner
Tired of copying queries from Slack, Jira, or AI chats only to encounter broken syntax caused by \_ and \* backslash escapes? Our tool detects and cleans them with one click.
1-Click Code Wrappers
Export your formatted SQL directly into native multiline strings for JavaScript/TypeScript, Python, Java 15+ Text Blocks, C# Raw String Literals, Go, Rust, and PHP Heredoc.
How Zero-Telemetry In-Browser Execution Safeguards Your Data
Most online developer utilities process user input through remote backend web APIs. When formatting internal SQL scripts containing proprietary schema definitions, financial calculations, HIPAA-regulated medical column names, or production data values, transmitting that code over third-party networks introduces severe compliance and infosec liabilities.
Our SQL query formatter operates under an uncompromising architecture: complete client isolation. The lexical tokenizer, dialect grammars, formatting rules, and visual diff algorithms are delivered as static web assets and run solely inside your web browser's local V8 or JavaScriptCore sandbox. Disconnecting your network connection verifies that full beautification, minification, and code exporting continue without interruption.
01 / Tokenization
Lexical stream generation isolates keywords, string literals, and parameters entirely within browser RAM.
02 / Tree Assembly
Dialect-specific grammar rules apply indentation depth, leading commas, and case transformations in milliseconds.
03 / Privacy Guarantee
Zero logs, zero network telemetry, and zero remote caching. Your database schemas remain confidential.
20種類以上のデータベースエンジンに対応
各データベース特有の予約語やクォート構文、組み込み関数に完全対応。
Standard ANSI SQL
Universal ISO/IEC SQL standard
PostgreSQL
Postgres 10+ with modern JSONB & window functions
MySQL
MySQL 5.7 / 8.0 syntax & functions
Microsoft SQL Server (T-SQL)
Transact-SQL with square brackets and CTEs
SQLite
Embedded lightweight SQL
Snowflake
Snowflake SQL with semi-structured expressions
Google BigQuery
GoogleSQL dialect with struct & arrays
Amazon Redshift
AWS analytics engine
Apache Spark SQL
Distributed Big Data queries
Trino / Presto
High performance SQL distributed engine
ClickHouse
Fast column-oriented OLAP DBMS
DuckDB
In-process analytical database
MariaDB
Community-developed MySQL fork
Oracle PL/SQL
Oracle Database procedural SQL
IBM DB2
Enterprise IBM relational database
SingleStoreDB
Real-time distributed SQL
TiDB
Distributed HTAP database
Couchbase N1QL
SQL for NoSQL documents
Apache Hive
Data warehouse query software for Hadoop
Can't find your specific dialect?
Standard ANSI SQL works across virtually all SQL-92, SQL:1999, and SQL:2016 compliant engines.
Dialect-Specific Syntax Differences Handled Automatically
Every database engine implements unique SQL standards extensions, quotation conventions, and reserved analytical keywords. Our query formatter applies specialized grammar models tailored to each engine:
Automatic handling of PostgreSQL double quotes ("col"), MySQL & BigQuery backticks (`table`), and Microsoft T-SQL square brackets ([field]).
Dedicated recognition for Snowflake QUALIFY and LATERAL FLATTEN, BigQuery struct unnesting, and Redshift distribution keys.
Formatting support for multi-statement DDL/DML batches, T-SQL GO batch separators, PL/SQL packages, and transaction blocks.
他社SQLフォーマッターとの違い
広告やデータ収集の一切ない、エンジニアファーストの快適な体験を提供します。
Looking for a modern Poor SQL (PoorSQL) or Instant SQL Formatter alternative?
Pioneering legacy tools like Poor Man's T-SQL Formatter (poorsql), dpriver Instant SQL Formatter, and generic code beautifiers paved the way. However, they frequently require server-side query submission, lack modern cloud dialects like Snowflake or BigQuery, or bombard users with ads. sqlqueryformatter.com is built from the ground up for modern engineering teams: 100% in-browser client execution, zero server transmission, leading comma styling, side-by-side visual diffs, and 20+ active database dialects.
SQLコーディング規約・スタイルガイド
チーム全体でSQL記法を統一することで、Gitマージ衝突を最小化します。
UPPERCASE SELECT & SQL Reserved Keywords
Standardizing SQL reserved keywords (SELECT, FROM, WHERE, JOIN) in uppercase while keeping table, schema, and column names in lowercase snake_case makes queries immediately scannable by human reviewers.
SELECT user_id, order_date
FROM customer_orders
WHERE status = 'active';
Why Leading Commas Win in Git Diffs
In trailing comma style, appending a new column modifies the previous line to add a trailing comma, resulting in two changed lines in Git pull requests. In comma-first style (, column_name), additions and deletions are strictly single-line diffs, eliminating merge conflicts.
SELECT
id
, name
, created_at
FROM users;
Modular CTEs over Deeply Nested Subqueries
Deeply nested inline subqueries quickly turn queries into unreadable spaghetti code. Decompose complex multi-step data pipelines into named Common Table Expressions (WITH clauses) to establish clear, top-to-bottom reading order.
WITH filtered_users AS (
SELECT id, email FROM users
)
SELECT * FROM filtered_users;
Explicit ANSI JOINs with Clear ON Conditions
Never use legacy comma-separated joins with filter predicates buried in the WHERE clause. Always write explicit INNER JOIN, LEFT JOIN, or CROSS JOIN keywords and place join predicates directly on the indented ON line.
FROM orders o
INNER JOIN customers c
ON c.id = o.customer_id;
Leading AND / OR Operators in WHERE Clauses
When chaining multiple filter conditions, start each condition line with the logical operator (AND, OR) rather than trailing it at the end. This structure highlights condition groupings and avoids accidental boolean logic bugs.
WHERE is_active = 1
AND region = 'US-East'
AND balance > 0;
Terminate with Semicolons & Space Comments
Always terminate statements with a semicolon (;), which is required by dialect parsers when chaining CTEs or executing batch migration scripts. For inline notes, use double dashes with a space (-- note) to prevent dialect syntax conflicts.
-- Step 1: Active customers
SELECT id FROM users WHERE active = 1;
-- Step 2: Recent transactions
SELECT * FROM transactions;
Why Formatting Conventions Matter for Database Performance and Team Productivity
Consistent SQL query formatting is not merely an aesthetic preference; it directly impacts database performance and maintenance velocity. Modern relational database management systems (RDBMS) like Oracle, Microsoft SQL Server, and PostgreSQL maintain internal query execution plan caches. Because plan cache lookups frequently rely on normalized SQL text hashing, inconsistent capitalization, erratic spacing, or scattered line breaks can prevent plan cache re-use, resulting in unnecessary query compilation overhead.
Furthermore, in engineering teams managing hundreds of database migration files, uniform SQL syntax reduces pull request cognitive fatigue. When teammates adopt standardized leading commas, predictable indentation depth (such as 2 or 4 spaces), and structured Common Table Expressions (CTEs), syntax errors and subtle join omissions are caught immediately during code review, preventing production schema rollbacks.
Q&A・よくある質問
プライバシー保護の仕組み、対応DB、各種機能に関する回答をまとめました。
Is this online SQL query formatter really 100% free with no limits?
Yes, sqlqueryformatter.com is a completely free online SQL formatter, beautifier, and query minifier. There are zero usage limits, no query length caps, no account registration requirements, and no hidden paywalls. Whether you need to format a 10-line ad-hoc query or refactor a 5,000-line enterprise database migration script, you can format, beautify, and minify unlimited SQL queries all day without restrictions.
How do I format and beautify SQL queries online?
To format your SQL query, paste your raw, messy, or minified SQL into the input editor pane. You can select your database dialect manually (PostgreSQL, MySQL, T-SQL, Snowflake, BigQuery, Oracle, SQLite, and 15+ others) or leave the selector on Auto-Detect. Choose your preferred indentation (2 spaces, 4 spaces, or tabs), keyword casing (UPPERCASE, lowercase, or preserve), and toggle leading comma (comma-first) formatting mode if desired. Click 'Format SQL' (or press Ctrl+Enter / Cmd+Enter) and your cleaned, formatted query appears instantly in the output editor.
Is this tool an alternative to Poor SQL (poorsql) or dpriver Instant SQL Formatter?
Yes! While Poor Man's T-SQL Formatter (poorsql) and dpriver Instant SQL Formatter were early solutions, sqlqueryformatter.com provides a modern, privacy-first, zero-telemetry alternative. Unlike legacy formatters that transmit queries over HTTP POST requests to remote backend servers, our tool executes 100% in your browser's local memory. Furthermore, we provide modern support for 20+ database engines (including cloud data warehouses like Snowflake, Google BigQuery, and Databricks Spark SQL), side-by-side visual diff checking, and 1-click code exports into 8 programming languages.
Is my SQL query safe and private when using this online SQL beautifier?
Yes, completely. Privacy and security are our core architectural tenets. All lexical parsing, dialect tokenization, syntax tree construction, and formatting operations run entirely within your web browser's local JavaScript V8 or JavaScriptCore sandbox. Your proprietary database schemas, confidential table names, internal column references, and sensitive data values never touch a remote server, external database, or third-party tracking script. You can disconnect your internet connection and verify that the formatter operates seamlessly offline.
Which database dialects does this SQL query formatter support?
We support over 20 distinct database dialects: Standard ANSI SQL, PostgreSQL, MySQL, MariaDB, Microsoft SQL Server (T-SQL), SQLite, Snowflake, Google BigQuery, Amazon Redshift, Oracle PL/SQL, Apache Spark SQL, Trino / Presto, IBM DB2, DuckDB, ClickHouse, TiDB, SingleStoreDB, Apache Hive, and Couchbase N1QL. Each dialect features custom quotation parsing (such as PostgreSQL double quotes, MySQL backticks, and T-SQL square brackets), specialized window clauses, and reserved analytical keywords.
Can this query beautifier handle messy, unformatted, or minified SQL queries?
Yes. Our parsing engine effortlessly normalizes single-line compressed queries, deeply nested subqueries, long comma-separated column lists, complex multi-table JOINs, recursive Common Table Expressions (WITH RECURSIVE clauses), and batch SQL migration scripts containing multiple statements separated by semicolons. It intelligently preserves inline comments, cleans malformed spacing, and standardizes indentation depth throughout the query hierarchy.
What is Comma-First (leading comma) formatting and why is it popular?
Comma-First (leading comma) formatting positions commas at the start of each column line (for example, ', column_name') rather than at the end of the preceding line. Data engineers, DBAs, and software developers widely favor this convention because it produces clean 1-line Git diffs when adding or deleting columns. In contrast, trailing comma style requires modifying the previous line to add a comma, generating two changed lines in pull requests and increasing the likelihood of merge conflicts.
How does the Markdown & Slack escape cleaner work?
When developers copy SQL queries out of team collaboration tools like Slack, Microsoft Teams, Jira, GitHub comments, or AI chat interfaces, special characters such as underscores and asterisks frequently get mangled with backslashes (such as 'user\_id' or 'COUNT(\*)'). When executed, these backslashes cause immediate SQL syntax errors. Our tool automatically scans pasted queries for these escape artifacts and cleans them with a single click.
How do I export formatted SQL queries into Python, JavaScript, Java, or C# code?
After formatting your SQL query, click the 'Export Code' button in the toolbar above the formatted output. You can choose from 8 popular programming languages: JavaScript/TypeScript (template literals), Python (triple-quoted strings), Java 15+ (text blocks), C# (raw string literals), Go (backtick multiline strings), Rust (raw string literals), and PHP (heredoc syntax). The modal generates properly escaped, production-ready multiline string snippets ready to paste directly into your repository.
Does formatting or beautifying SQL queries alter query execution performance?
No. The formatter only restructures whitespace, line breaks, indentation levels, and keyword capitalization. It never modifies your underlying relational logic, table joins, index filter predicates, or literal parameter values. Your database engine's query optimizer will generate the exact same relational algebra and execution plan. In fact, standardizing SQL casing and spacing across your application helps RDBMS query plan caches locate matching compiled plans more efficiently.
How does the static dialect auto-detection work?
Our auto-detection algorithm performs lexical heuristic analysis directly inside your browser. It inspects query tokens for syntax markers unique to specific engines—such as Snowflake's QUALIFY clause and colon JSON navigation, BigQuery's backtick dataset quoting, PostgreSQL's double-colon type casts, and SQL Server's square bracket delimiters. This static analysis achieves high accuracy without transmitting query text over the network.
Does sqlqueryformatter.com store cookies or track my activity?
We do not store cookies or track your browsing activity. We do not use third-party behavioral analytics or session replay recorders. Your theme choice (dark mode or light mode) is saved exclusively in your browser's local storage (localStorage) on your device. We believe developer utilities should be fast, respectful, and completely private by default.