Free ClickHouse SQL Formatter & Beautifier Online
High-speed SQL formatting optimized for ClickHouse analytical queries, arrays, and PREWHERE clauses. AST-verified formatting with Monaco Git Diff inspection.
About ClickHouse SQL formatting
ClickHouse SQL is optimized for analytical scans and has syntax that reflects its columnar execution model. PREWHERE can be more selective than WHERE, ARRAY JOIN expands nested arrays, and aggregate combinators add suffixes such as -State, -Merge, or -If to otherwise familiar functions. Queries also use tuple and array literals, lambda expressions, sampling clauses, and table functions. These details make a flat keyword-based formatter especially poor at showing the relationship between an analytical source and its transformations.
This ClickHouse formatter gives PREWHERE, WHERE, GROUP BY, HAVING, and ORDER BY a stable visual order while preserving ClickHouse-specific function names. Nested aggregation expressions remain grouped, array operations stay attached to their source columns, and analytical aliases remain readable in later clauses. The formatter also handles common DDL and operational statements, so a script containing table definitions, inserts, or maintenance commands can be reviewed without losing statement boundaries.
It preserves the distinction between a columnar optimization hint and a result-set filter, which is often the first thing a performance review needs to establish.
Use the preset example to see a time-bucketed event query with PREWHERE, a subquery, quantiles, array aggregation, and a row limit. It is useful for query reviews, materialized-view work, and dashboards where small layout changes can hide a significant scan or grouping operation. Format the draft, open View Git Diff, and verify the changes before copying the final ClickHouse SQL.
Because ClickHouse queries often grow through successive analytical expressions, the page favors visible clause boundaries over aggressive compaction. That gives reviewers a better view of filters that reduce scanned data, groupings that change cardinality, and array operations that can expand a result unexpectedly.
This is valuable for teams sharing SQL between the ClickHouse console, dashboards, and version-controlled materialized views. The output stays close to the source query while making its execution-oriented stages easier to discuss during review.
What's different about ClickHouse formatting? ClickHouse formatting distinguishes PREWHERE from WHERE and keeps ARRAY JOIN and analytical aggregate expressions easy to scan. Example: SELECT toDate(event_time), count() FROM events PREWHERE event_date >= today() - 7 GROUP BY toDate(event_time);
ClickHouse formatting highlights
- ClickHouse PREWHERE and WHERE clauses
- Nested aggregation combinators (-State, -Merge, -ExactWeighted)
- Array manipulation and lambda functions
- DateTime functions and interval expressions
ClickHouse array and tuple brackets are preserved deterministically. The editor above is already configured for ClickHouse; format the included sample or replace it with a query from your own project.
ClickHouse formatter FAQ
Does it support PREWHERE clauses?
Yes, ClickHouse PREWHERE optimization clauses are supported and indented correctly.
Need another engine? Browse the multi-dialect SQL formatter or choose a related dialect below.
Supported SQL Dialects & Engines
Format SQL queries across standard and cloud database dialects using native parser engines and AST-based formatting.
Best-in-class GoogleSQL formatting with native AST engine, pipe syntax support, and zero SQL storage.
Format PostgreSQL queries with support for JSONB, recursive CTEs, and advanced analytical window functions.
Beautify MySQL queries, backtick identifiers, and stored procedure blocks with clean indentation.
Microsoft ScriptDOM formatting for SQL Server and T-SQL, with versioned grammar, brackets, and CROSS APPLY joins.
High-speed SQL formatting optimized for ClickHouse analytical queries, arrays, and PREWHERE clauses.
Format Snowflake SQL queries and semi-structured expressions.
Format DuckDB queries and analytical transformations.
Format SQLite SQL queries, schemas, and triggers with clean indentation.
Format Oracle SQL queries with support for JSON_TABLE, CONNECT BY hierarchies, and analytical functions.
Format Databricks SQL, Delta Lake time travel (TIMESTAMP AS OF), STRUCT literals, and LATERAL VIEWs.
Format Apache Spark SQL queries, LATERAL VIEWs, struct access, and window transformations.
Format HiveQL queries, LATERAL VIEWs, PARTITION BY, and CLUSTER BY clauses.
Format Amazon Redshift analytical queries, VACUUM, and window functions.
Standard ANSI SQL formatting that works universally across database engines and query editors.