Free Oracle SQL Formatter Online - PL/SQL & SQL Beautifier

Format Oracle SQL queries with support for JSON_TABLE, CONNECT BY hierarchies, and analytical functions. AST-verified formatting with Monaco Git Diff inspection.

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About Oracle SQL SQL formatting

Oracle SQL has a long history of specialized query features that still appear in production systems. Hierarchical queries use START WITH and CONNECT BY PRIOR, pagination may use ROWNUM or FETCH FIRST, and JSON_TABLE projects document fields into relational columns. Oracle also supports analytical functions, MODEL clauses, q-quoted strings, hints, and PL/SQL-adjacent scripts. These constructs need deliberate indentation because their order and nesting carry meaning beyond ordinary SELECT formatting.

This Oracle formatter keeps hierarchical and analytical clauses attached to the query they control. JSON_TABLE column definitions are laid out as a nested schema, window frames remain readable, and CONNECT BY relationships are not confused with ordinary joins. Quoted strings, hints, aliases, and Oracle’s uppercase identifier convention are preserved while CTEs, subqueries, CASE expressions, and pagination clauses receive consistent spacing and line breaks.

The Oracle sample combines a recursive-looking employee hierarchy, CONNECT BY, JSON_TABLE, an analytic average, and an ordering limit. Start there when evaluating the formatter for a reporting query, stored procedure, or migration. The editor is preconfigured for Oracle on this URL, and the formatted-output diff provides a quick way to confirm that the query’s hierarchy and JSON projection remain recognizable after cleanup.

That makes the page a useful first check before standardizing a team’s Oracle SQL review style.

Oracle queries can be difficult to review when a JSON projection and a hierarchical source are compressed into one line. Separating those structures gives database teams a dependable view of join conditions, path columns, analytic frames, and row limits before a report or procedure is promoted.

Use the output as a review aid rather than as a migration between Oracle and another engine. Oracle’s hints, hierarchy rules, and JSON column definitions remain dialect-specific; the formatter’s job is to make those choices legible and stable.

What's different about Oracle formatting? Oracle formatting keeps CONNECT BY hierarchy, JSON_TABLE columns, and analytic functions attached to the clauses that control them. Example: SELECT employee_id, LEVEL FROM employees START WITH manager_id IS NULL CONNECT BY PRIOR employee_id = manager_id;

Oracle formatting highlights

  • Oracle JSON_TABLE and JSON path queries
  • Hierarchical queries (START WITH ... CONNECT BY PRIOR)
  • Analytical window functions with custom framing
  • Quote-delimited string literals (q'[...]')
  • ROWNUM and FETCH FIRST ... ROWS ONLY pagination

Oracle defaults unquoted identifiers to UPPERCASE. The editor above is already configured for Oracle SQL; format the included sample or replace it with a query from your own project.

Oracle formatter FAQ

Does it support Oracle JSON_TABLE and hierarchical queries?

Yes, Oracle JSON_TABLE expressions and START WITH / CONNECT BY clauses are fully supported and indented cleanly.

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.

BigQuery (GoogleSQL)GoogleSQL

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MySQLSQLFusion

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SQL Server (T-SQL)ScriptDOM

Microsoft ScriptDOM formatting for SQL Server and T-SQL, with versioned grammar, brackets, and CROSS APPLY joins.

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ClickHouseSQLFusion

High-speed SQL formatting optimized for ClickHouse analytical queries, arrays, and PREWHERE clauses.

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SnowflakeSQLFusion

Format Snowflake SQL queries and semi-structured expressions.

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DuckDBSQLFusion

Format DuckDB queries and analytical transformations.

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SQLiteSQLFusion

Format SQLite SQL queries, schemas, and triggers with clean indentation.

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Oracle SQLSQLFusion

Format Oracle SQL queries with support for JSON_TABLE, CONNECT BY hierarchies, and analytical functions.

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Databricks SQLSQLFusion

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SparkSQLSQLFusion

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Apache HiveSQLFusion

Format HiveQL queries, LATERAL VIEWs, PARTITION BY, and CLUSTER BY clauses.

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Amazon RedshiftSQLFusion

Format Amazon Redshift analytical queries, VACUUM, and window functions.

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Generic / ANSI SQLSQLFusion

Standard ANSI SQL formatting that works universally across database engines and query editors.

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