An RDBMS-agnostic SQL parser for the JVM: |  |
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Give it SQL. Get an AST you can walk, rewrite, and print back out.
SELECT1FROM dual WHERE a = bSQL Text
└─Statements: statement.select.PlainSelect
├─selectItems: statement.select.SelectItem
│ └─LongValue: 1
├─Table: dual
└─where: expression.operators.relational.EqualsTo
├─Column: a
└─Column: b
StringsqlStr = "select 1 from dual where a=b";
PlainSelectselect = (PlainSelect) CCJSqlParserUtil.parse(sqlStr);
SelectItemselectItem = select.getSelectItems().get(0);
Assertions.assertEquals(newLongValue(1), selectItem.getExpression());
Tabletable = (Table) select.getFromItem();
Assertions.assertEquals("dual", table.getName());
EqualsToequalsTo = (EqualsTo) select.getWhere();
Columna = (Column) equalsTo.getLeftExpression();
Columnb = (Column) equalsTo.getRightExpression();
Assertions.assertEquals("a", a.getColumnName());
Assertions.assertEquals("b", b.getColumnName());The tree is traversable with the Visitor pattern, and the same object model works in reverse: build statements from Java with a fluent API and render them as SQL text.
Use the stable Manticore builds. They are released continuously from the current development
line and carry all of the performance and grammar work described below. The upstream
com.github.jsqlparser release on Maven Central is considerably older.
<dependency>
<groupId>com.manticore-projects.jsqlformatter</groupId>
<artifactId>jsqlparser</artifactId>
<version>[5.3.218,)</version>
</dependency>implementation("com.manticore-projects.jsqlformatter:jsqlparser:+")Upstream release and snapshots
<dependency>
<groupId>com.github.jsqlparser</groupId>
<artifactId>jsqlparser</artifactId>
<version>5.3</version>
</dependency>Snapshot coordinates and repository setup are on the build dependencies page.
11× faster than 5.3, and the fastest parser on real-world SQL of any of the parsers
tested, in any language — 19× ahead of sqlglot[c] on JSqlParser's own SELECT test suite.
Benchmark (version) Mode Cnt Score Error Units
JSQLParserBenchmark.parseSQLStatements latest avgt 15 7.602 ± 0.135 ms/op
JSQLParserBenchmark.parseSQLStatements 5.3 avgt 15 84.687 ± 3.321 ms/op
Methodology and the full cross-parser comparison against SQLGlot, sqlglot[c] and
polyglot-sql: jsqlparser-bench.
JSqlParser targets the SQL standard plus all major RDBMS. One grammar covers all of them, and missing syntax gets added on demand — open an issue.
BigQuery · Snowflake · DuckDB · Redshift · Oracle · MS SQL Server · SybasePostgreSQL · MySQL · MariaDB · DB2 · H2 · HSQLDB · Derby · SQLite
| Statements | |
|---|---|
| Queries | SELECT · WITH … · Piped SQL |
| DML | INSERT · UPDATE · UPSERT · MERGE · DELETE · TRUNCATE TABLE |
| DDL | CREATE … · ALTER … · DROP … |
| PostgreSQL RLS | CREATE POLICY · ALTER TABLE … ENABLE/DISABLE/FORCE/NO FORCE ROW LEVEL SECURITY |
| Salesforce SOQL | INCLUDES · EXCLUDES |
Beyond statement shapes, the grammar handles nested sub-selects, bind parameters (?,
:name), window and analytic functions, Oracle hints, and the T-SQL square-bracket versus
array-literal ambiguity. The complete reference is on the
syntax page.
Support is progressing for Piped SQL, which writes queries in the order they actually execute rather than the order SQL historically demanded.
FROM Produce
|>WHERE
item !='bananas'AND category IN ('fruit', 'nut')
|> AGGREGATE COUNT(*) AS num_items, SUM(sales) AS total_sales
GROUP BY item
|>ORDER BY item DESC;Background reading: the Google research paper, BigQuery pipe syntax and DuckDB FROM-first syntax.
| JSqlParser | Runtime | Notes |
|---|---|---|
| 4.9 | JDK 8 | last JDK 8 compatible release |
| 5.0 and later | JDK 11 | breaking changes to the AST Visitors, see the Migration Guide |
| 5.1 and later | JDK 11 | building requires a JDK 17 toolchain (plugin requirement) |
| 5.4 and later | JDK 11 | parser generated with JavaCC 8 |
- JSQLFormatter — pretty-printing and formatting of SQL text
- JSQLTranspiler — dialect-specific rewriting, column resolution and lineage, by Starlake.ai
The dual-licensed JOOQ ships a hand-written parser with broad RDBMS support, cross-dialect translation, SQL transformation, and a JDBC proxy mode. Worth a look if translation between dialects is your primary need rather than AST access.
A huge thank you to Starlake.ai, who simplify data ingestion, transformation and orchestration for faster delivery of high-quality data. Starlake has been instrumental in providing Piped SQL support and a large number of test cases for BigQuery, Redshift, Databricks and DuckDB. If JSqlParser is useful to you, visit Starlake.ai and give them a star.
Dual licensed under LGPL 2.1 or the Apache License, Version 2.0. Take your pick.