Parsing SQL in Java depends heavily on your use case: do you need a lightweight tool to extract table names, or a full-blown query engine to optimize and execute queries?

Here are the top 10 solutions for parsing SQL in Java, categorized by their strengths and use cases.

1. JSqlParser (Top Choice for General Use)

JSqlParser is the most popular open-source library for Java. It uses JavaCC to translate SQL into a hierarchy of Java classes, allowing you to navigate the structure using the Visitor Pattern.

• Best for: Modifying SQL, extracting metadata (tables, columns), and simple SQL translation.

• Pros: RDBMS agnostic; supports MySQL, PostgreSQL, Oracle, SQL Server, and BigQuery.

• Cons: Not a validator; it may accept syntactically incorrect SQL if the grammar isn’t strict.

2. Apache Calcite

Calcite is a dynamic data management framework. It doesn’t just parse; it provides a full SQL parser, validator, and cost-based optimizer.

• Best for: Building your own database/query engine or performing deep semantic analysis.

• Pros: Industry standard used by Apache Hive, Flink, and Druid.

• Cons: Very steep learning curve; high resource overhead for simple tasks.

3. jOOQ (Parser API)

While famous as a DSL for writing SQL, jOOQ includes a powerful standalone parser. It can take a raw SQL string and convert it into a jOOQ Query object.

• Best for: Dialect transpilation (e.g., converting Oracle SQL to PostgreSQL) and type-safe query manipulation.

• Pros: Extremely robust; handles complex vendor-specific syntax.

• Cons: Commercial license required for some features; library size is large.

4. General SQL Parser (GSP)

A commercial powerhouse, GSP is known for its incredible breadth of dialect support and deep analysis capabilities.

• Best for: Enterprise-grade data lineage, SQL formatting, and complex refactoring.

• Pros: Supports over 20+ dialects (Snowflake, Hive, Teradata, etc.) better than most open-source tools.

• Cons: Expensive commercial license.

5. ANTLR (with Community SQL Grammars)

ANTLR is a parser generator. You don’t get a “SQL library” out of the box; instead, you take a .g4 grammar file (for MySQL, PL/SQL, etc.) and generate the Java code.

• Best for: Custom SQL-like languages or when you need total control over the parsing logic.

• Pros: Highly flexible; generate parsers in multiple languages.

• Cons: High manual effort; you must maintain the grammar files yourself.

6. H2 Database Parser

The H2 Database is written in Java and contains its own internal recursive-descent parser. You can use its internal classes (like org.h2.command.Parser) to parse SQL.

• Best for: Projects already using H2 or needing a high-speed, hand-written parser.

• Pros: Very fast and battle-tested in a production database.

• Cons: Not designed as a standalone library; internal APIs can change.

7. ZetaSQL

Developed by Google, ZetaSQL is the parser used for BigQuery and Spanner. It has been open-sourced with Java wrappers.

• Best for: Projects that need to be 100% compatible with Google Cloud’s SQL dialect.

• Pros: Precise semantic analysis and strict validation.

• Cons: Primarily focused on the “GoogleSQL” dialect; complex setup.

8. Druid SQL Parser

Apache Druid contains a specialized parser built on Calcite but optimized for its own analytical needs.

• Best for: Big data analytics and time-series query parsing.

• Pros: Excellent performance for analytical (OLAP) queries.

9. Zql (The “Old School” Choice)

Zql is a lightweight SQL parser written in JavaCC. It is much simpler (and older) than JSqlParser.

• Best for: Very small, legacy, or resource-constrained applications.

• Pros: Minimal footprint.

• Cons: Not updated frequently; lacks support for modern SQL features like Window Functions or JSON operators.

10. Presto/Trino Parser

Trino (formerly Presto) has a highly efficient, hand-written parser designed to handle massive scale.

• Best for: High-performance distributed query processing.

• Pros: Clean Abstract Syntax Tree (AST) for complex SELECT statements.

Comparison Summary

Would you like me to provide a code example for one of these, such as using JSqlParser to extract table names from a query?