This post is maintained by Bytebase, an open-source database DevSecOps tool that can manage all mainstream databases, we have built various database-specific parsers to support features like SQL Review. We update the post every year.
| Update History | Comment |
|---|---|
| 2025/04/16 | Initial version. |
| 2025/04/21 | Fix wrong link. |
SQL (Structured Query Language) remains the dominant language for database interactions, powering everything from traditional relational databases to modern data warehouses and analytics platforms. Behind the scenes, SQL parsers play a crucial role in interpreting, validating, and processing SQL statements.
In this blog post, we'll explore the top open source SQL parsers available in 2025, categorizing them into database-specific parsers and generic parsers. We'll also take a look at ANTLR, a powerful parser generator that's commonly used to build custom SQL parsers.
What is a SQL Parser?
A SQL parser is a software component that reads SQL text and converts it into a structured representation, typically an Abstract Syntax Tree (AST). This structured representation makes it possible to:
- Validate SQL syntax without executing the query
- Format and pretty-print SQL statements
- Analyze query patterns and identify potential issues
- Transform queries for optimization or dialect conversion
- Extract metadata such as table and column references
- Track data lineage and dependencies
SQL parsers are used in a wide range of applications, including:
- Database management systems
- SQL editors and IDEs
- Query optimization tools
- Data lineage and governance platforms
- Migration tools for moving between database systems
- Educational platforms for teaching SQL
MySQL/MariaDB Parsers
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TiDB Parser by PingCAP. Written in Go, it's the most widely adopted MySQL parsers, many backend application uses it. The downside is it's a parser for TiDB and has compatibility limitations such as the lack of stored procedure support.
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sql-parser in phpMyAdmin. Written in PHP, it's a by-product of the mighty phpmyadmin with good MySQL compatibility support.
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mysql-parser by Bytebase. Written in Go based on ANTLR with good MySQL compatibility support.
PostgreSQL Parsers
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libpg_query by pganalyze. This is not a parser by itself. It's a C library that facilitates building the language-binding parsers such as:
- Python: pglast
- Ruby: pg_query
- Golang: pg_query_go
- JavaScript: psql-parser
- Rust: pg_query.rs
Oracle Parsers
- plsql-parser. Go-based parser based on the ANTLR Oracle grammar.
SQL Server Parsers
- tsql-parser. Go-based parser based on the ANTLR T-SQL grammar.
General-Purpose Parsers
Building a general-purpose SQL parser that robustly supports multiple databases is inherently challenging, as each database system has its unique dialect and syntax variations.
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sqlparser-rs. A rust-based parser which is used by many rust-based database project. Its readme is honest about the compatibility limitation. Still, it's the most promising one.
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JSqlParser. A java-based parser supporting Oracle, SQL Server, MySQL, PostgreSQL, and etc. Though the supported syntax is limited
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ZetaSQL. A unified parser implements the GoogleSQL language, which is used across several of Google's SQL products, including BigQuery, Spanner, F1, BigTable.
ANTLR as a SQL Parser Generator
While database-specific and generic SQL parsers provide ready-to-use solutions for common SQL dialects, sometimes you need to create a custom parser for a specific SQL dialect or extend an existing one. ANTLR (ANother Tool for Language Recognition) shines in these scenarios, serving as a robust parser generator for SQL grammar.
One of ANTLR's greatest strengths is its ability to generate parsers in multiple target languages. ANTLR uses grammar files (with a .g4 extension) to define language syntax. These grammar files are human-readable and serve as both documentation and code. For SQL parsing, you can either:
- Use existing SQL grammar files from the community
- Modify existing grammars to support specific SQL dialect features
- Create your own grammar from scratch for highly specialized SQL dialects
At Bytebase, we build the database-specific parsers based on the community grammar file. Despite challenges—particularly around performance, we've found this to be the most effective approach.
Final Thoughts
SQL parsers may seem like a niche technical component, but they play a crucial role in database tools, query editors, data lineage systems, and many other applications.
Whether you opt for a database-specific parser for precise dialect support, a generic parser for flexibility across multiple databases, or ANTLR for custom parsing needs, we hope this overview helps you navigate the landscape of SQL parsers and find the right solution for your specific requirements.
