SQL Parser & Analyzer
Parse and analyze SQL code structure. Tokenize queries, build Abstract Syntax Trees, and understand your SQL at a deeper level.
Parser Settings
AST Mode
Generates an Abstract Syntax Tree showing the query structure.
SQL Code
Parse Results
Parse results will appear here...
Click "Parse SQL Code" to analyze your SQL query structure
SQL Parser Tool – Analyze Query Structure & Components
The SQL Parser Tool provides deep analysis of SQL code by breaking it down into tokens or building an Abstract Syntax Tree (AST). This helps developers understand query structure, identify components, and gain insights for optimization and debugging.
What is SQL Parsing?
SQL parsing is the process of analyzing SQL statements to understand their structure and meaning. Parsers can work at different levels:
Lexical Analysis (Tokenization)
Breaks SQL code into individual tokens - the smallest meaningful units like keywords, identifiers, operators, and literals.
- Identifies SQL keywords (SELECT, FROM, WHERE)
- Extracts table and column names
- Recognizes string and numeric literals
- Detects operators and punctuation
- Separates comments from code
Syntactic Analysis (AST Building)
Creates a hierarchical tree structure showing how tokens relate to each other and form valid SQL constructs.
- Builds query structure hierarchy
- Shows clause relationships
- Identifies subquery nesting
- Maps JOIN relationships
- Validates syntax structure
Parser Features
- Dual Mode Analysis – Choose between tokenization and AST building
- Token Classification – Identifies keywords, identifiers, strings, numbers, comments
- AST Visualization – Hierarchical view of query structure
- Detailed Statistics – Counts and categorizes all query elements
- Clause Identification – Automatically identifies SELECT, FROM, WHERE, etc.
- Join Detection – Counts and identifies JOIN operations
- Function Recognition – Identifies SQL functions and aggregates
- Metadata Extraction – Extracts tables, columns, aliases, conditions
Tokenization Mode
In tokenization mode, the parser breaks your SQL into individual tokens and classifies them:
Keywords
SQL reserved words like SELECT, FROM, WHERE
Color: BlueIdentifiers
Table and column names, aliases
Color: GreenLiterals
String and numeric constants
Color: YellowAST (Abstract Syntax Tree) Mode
In AST mode, the parser builds a hierarchical tree structure showing your query's syntax:
- Root Node – The entire SQL query
- Clause Nodes – SELECT, FROM, WHERE, GROUP BY, etc.
- Expression Nodes – Column references, functions, operations
- Condition Nodes – WHERE and HAVING conditions
- Join Nodes – JOIN operations and relationships
- Subquery Nodes – Nested SELECT statements
Use Cases for SQL Parsing
- Query Analysis – Understand complex query structure
- Code Reviews – Analyze SQL code during reviews
- Learning Tool – Study SQL syntax and structure
- Optimization – Identify optimization opportunities
- Documentation – Generate documentation from SQL
- Migration – Analyze SQL before database migration
- Security – Identify potentially problematic patterns
- Tool Development – Basis for SQL-related tools
Parser Limitations
This is a web-based parser with some limitations:
- Does not validate against actual database schemas
- May not recognize all database-specific extensions
- Cannot execute or validate query results
- Limited handling of extremely complex nested queries
- Basic error detection only (not comprehensive)
For production use or complex analysis, consider dedicated SQL parsing libraries or database-specific tools.
Privacy & Security
All parsing happens in your browser. No SQL code is sent to any server, ensuring complete privacy and security for your database queries and schemas.
