GoSQLX

⚡ High-Performance SQL Parser for Go ⚡

Production-ready, high-performance SQL parsing SDK for Go
Zero-copy tokenization • Object pooling • Multi-dialect support • Unicode-first design

🚀 New to GoSQLX? Get Started in 5 Minutes →

📖 Installation • ⚡ Quick Start • 📚 Documentation • 💡 Examples • 📊 Benchmarks

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Overview

GoSQLX is a high-performance SQL parsing library designed for production use. It provides zero-copy tokenization, intelligent object pooling, and comprehensive SQL dialect support while maintaining a simple, idiomatic Go API.

Key Features

• Blazing Fast: 1.38M+ ops/sec sustained, 1.5M+ ops/sec peak throughput
• Memory Efficient: 60-80% reduction through intelligent object pooling
• Thread-Safe: Race-free, linear scaling to 128+ cores, 0 race conditions detected
• Production-Grade Testing: Token 100%, Keywords 100%, Errors 95.6%, Tokenizer 76.1%, Parser 76.1%, CLI 63.3% coverage
• Complete JOIN Support: All JOIN types (INNER/LEFT/RIGHT/FULL OUTER/CROSS/NATURAL) with proper tree logic
• Advanced SQL Features: CTEs with RECURSIVE support, Set Operations (UNION/EXCEPT/INTERSECT)
• Window Functions: Complete SQL-99 window function support with OVER clause, PARTITION BY, ORDER BY, frame specs
• MERGE Statements: Full SQL:2003 MERGE support with WHEN MATCHED/NOT MATCHED clauses
• Grouping Operations: GROUPING SETS, ROLLUP, CUBE (SQL-99 T431)
• Materialized Views: CREATE, DROP, REFRESH MATERIALIZED VIEW support
• Table Partitioning: PARTITION BY RANGE, LIST, HASH support
• SQL Injection Detection: Built-in security scanner (pkg/sql/security) for injection pattern detection
• Unicode Support: Complete UTF-8 support for international SQL
• Multi-Dialect: PostgreSQL, MySQL, SQL Server, Oracle, SQLite
• PostgreSQL Extensions: LATERAL JOIN, DISTINCT ON, FILTER clause, JSON/JSONB operators, aggregate ORDER BY
• Zero-Copy: Direct byte slice operations, <1μs latency
• Intelligent Errors: Structured error codes with typo detection, context highlighting, and helpful hints
• Production Ready: Battle-tested with 0 race conditions detected, ~80-85% SQL-99 compliance

Performance & Quality Highlights (v1.6.0)

1.38M+	8M+	<1μs	14x	575x	100% ⭐
Ops/sec	Tokens/sec	Latency	Faster Tokens	Cache Speedup	Token Coverage

✅ v1.6.0 Released • LSP Server • VSCode Extension • PostgreSQL JSON/JSONB • 10 Linter Rules • ~85% SQL-99 compliance

🎉 What's New in v1.6.0

Feature	Description
🔌 LSP Server	Full Language Server Protocol for IDE integration with diagnostics, completion, hover
📝 VSCode Extension	Official extension with syntax highlighting, formatting, and autocomplete
🐘 PostgreSQL Extensions	LATERAL JOIN, JSON/JSONB operators (->, ->>, @>, #>), DISTINCT ON, FILTER clause
🔍 Linter Rules	10 built-in rules (L001-L010) with auto-fix for SELECT *, missing aliases, etc.
🛡️ Security Scanner	Enhanced SQL injection detection with severity classification
⚡ Performance	14x faster token comparison, 575x faster keyword suggestions via caching
🏗️ go-task	Modern task runner (Taskfile.yml) replacing Makefile
🔢 Structured Errors	Error codes E1001-E3004 for tokenizer, parser, and semantic errors

See CHANGELOG.md for the complete list of 20+ PRs merged in this release.

Project Stats

Installation

Library Installation

go get github.com/ajitpratap0/GoSQLX

CLI Installation

# Install the CLI tool
go install github.com/ajitpratap0/GoSQLX/cmd/gosqlx@latest

# Or build from source
git clone https://github.com/ajitpratap0/GoSQLX.git
cd GoSQLX
go build -o gosqlx ./cmd/gosqlx

Requirements:

• Go 1.24 or higher
• No external dependencies

Quick Start

CLI Usage

Standard Usage:

# Validate SQL syntax
gosqlx validate "SELECT * FROM users WHERE active = true"

# Format SQL files with intelligent indentation
gosqlx format -i query.sql

# Analyze SQL structure and complexity
gosqlx analyze "SELECT COUNT(*) FROM orders GROUP BY status"

# Parse SQL to AST representation
gosqlx parse -f json complex_query.sql

# Unix Pipeline Support
cat query.sql | gosqlx format                    # Format from stdin
echo "SELECT * FROM users" | gosqlx validate     # Validate from pipe
gosqlx format query.sql | gosqlx validate        # Chain commands
cat *.sql | gosqlx format | tee formatted.sql    # Pipeline composition

Pipeline/Stdin Support (New in v1.6.0):

# Auto-detect piped input
echo "SELECT * FROM users" | gosqlx validate
cat query.sql | gosqlx format
cat complex.sql | gosqlx analyze --security

# Explicit stdin marker
gosqlx validate -
gosqlx format - < query.sql

# Input redirection
gosqlx validate < query.sql
gosqlx parse < complex_query.sql

# Full pipeline chains
cat query.sql | gosqlx format | gosqlx validate
echo "select * from users" | gosqlx format > formatted.sql
find . -name "*.sql" -exec cat {} \; | gosqlx validate

# Works on Windows PowerShell too!
Get-Content query.sql | gosqlx format
"SELECT * FROM users" | gosqlx validate

Cross-Platform Pipeline Examples:

# Unix/Linux/macOS
cat query.sql | gosqlx format | tee formatted.sql | gosqlx validate
echo "SELECT 1" | gosqlx validate && echo "Valid!"

# Windows PowerShell
Get-Content query.sql | gosqlx format | Set-Content formatted.sql
"SELECT * FROM users" | gosqlx validate

# Git hooks (pre-commit)
git diff --cached --name-only --diff-filter=ACM "*.sql" | \
  xargs cat | gosqlx validate --quiet

Language Server Protocol (LSP) (v1.6.0):

# Start LSP server for IDE integration
gosqlx lsp

# With debug logging
gosqlx lsp --log /tmp/gosqlx-lsp.log

The LSP server provides real-time SQL intelligence for IDEs:

• Diagnostics: Real-time syntax error detection with position info
• Hover: Documentation for 60+ SQL keywords
• Completion: 100+ SQL keywords, functions, and 22 snippets
• Formatting: SQL code formatting via textDocument/formatting
• Document Symbols: SQL statement outline navigation
• Signature Help: Function signatures for 20+ SQL functions
• Code Actions: Quick fixes (add semicolon, uppercase keywords)

Linting (v1.6.0):

# Run built-in linter rules
gosqlx lint query.sql

# With auto-fix
gosqlx lint --fix query.sql

# Specific rules
gosqlx lint --rules L001,L002,L003 query.sql

Available rules (L001-L010):

• L001: Avoid SELECT *
• L002: Missing table aliases in JOIN
• L003: Implicit column aliases
• L004: Missing WHERE clause in UPDATE/DELETE
• L005: Inefficient LIKE patterns
• L006: Use explicit JOIN syntax (not comma joins)
• L007: ORDER BY ordinal numbers
• L008: Inconsistent keyword casing
• L009: Missing column list in INSERT
• L010: Avoid DISTINCT without ORDER BY

IDE Integration:

// VSCode settings.json
{
  "gosqlx.lsp.enable": true,
  "gosqlx.lsp.path": "gosqlx"
}

-- Neovim (nvim-lspconfig)
require('lspconfig.configs').gosqlx = {
  default_config = {
    cmd = { 'gosqlx', 'lsp' },
    filetypes = { 'sql' },
    root_dir = function() return vim.fn.getcwd() end,
  },
}
require('lspconfig').gosqlx.setup{}

Library Usage - Simple API

GoSQLX provides a simple, high-level API that handles all complexity for you:

package main

import (
    "fmt"
    "log"

    "github.com/ajitpratap0/GoSQLX/pkg/gosqlx"
)

func main() {
    // Parse SQL in one line - that's it!
    ast, err := gosqlx.Parse("SELECT * FROM users WHERE active = true")
    if err != nil {
        log.Fatal(err)
    }

    fmt.Printf("Successfully parsed %d statement(s)\n", len(ast.Statements))
}

That's it! Just 3 lines of code. No pool management, no manual cleanup - everything is handled for you.

More Examples

// Validate SQL without parsing
if err := gosqlx.Validate("SELECT * FROM users"); err != nil {
    fmt.Println("Invalid SQL:", err)
}

// Parse multiple queries efficiently
queries := []string{
    "SELECT * FROM users",
    "SELECT * FROM orders",
}
asts, err := gosqlx.ParseMultiple(queries)

// Parse with timeout for long queries
ast, err := gosqlx.ParseWithTimeout(sql, 5*time.Second)

// Parse from byte slice (zero-copy)
ast, err := gosqlx.ParseBytes([]byte("SELECT * FROM users"))

Advanced Usage - Low-Level API

For performance-critical code that needs fine-grained control, use the low-level API:

package main

import (
    "fmt"

    "github.com/ajitpratap0/GoSQLX/pkg/sql/tokenizer"
    "github.com/ajitpratap0/GoSQLX/pkg/sql/parser"
)

func main() {
    // Get tokenizer from pool (always return it!)
    tkz := tokenizer.GetTokenizer()
    defer tokenizer.PutTokenizer(tkz)

    // Tokenize SQL
    sql := "SELECT id, name FROM users WHERE age > 18"
    tokens, err := tkz.Tokenize([]byte(sql))
    if err != nil {
        panic(err)
    }

    // Convert tokens
    converter := parser.NewTokenConverter()
    result, err := converter.Convert(tokens)
    if err != nil {
        panic(err)
    }

    // Parse to AST
    p := parser.NewParser()
    defer p.Release()

    ast, err := p.Parse(result.Tokens)
    if err != nil {
        panic(err)
    }

    fmt.Printf("Statement type: %T\n", ast)
}

Note: The simple API has < 1% performance overhead compared to low-level API. Use the simple API unless you need fine-grained control.

Documentation

Comprehensive Guides

Guide	Description
Getting Started	Get started in 5 minutes
Comparison Guide	GoSQLX vs SQLFluff, JSQLParser, pg_query
CLI Guide	Complete CLI documentation and usage examples
API Reference	Complete API documentation with examples
Usage Guide	Detailed patterns and best practices
Architecture	System design and internal architecture
Troubleshooting	Common issues and solutions

Getting Started

Document	Purpose
Production Guide	Deployment and monitoring
SQL Compatibility	Dialect support matrix
Security Analysis	Security assessment
Examples	Working code examples

Quick Links

• Installation & Setup
• Basic Usage
• Advanced Patterns
• Performance Tuning
• Error Handling
• FAQ

Advanced SQL Features (v1.2.0)

GoSQLX now supports Common Table Expressions (CTEs) and Set Operations alongside complete JOIN support:

Common Table Expressions (CTEs)

// Simple CTE
sql := `
    WITH sales_summary AS (
        SELECT region, SUM(amount) as total 
        FROM sales 
        GROUP BY region
    ) 
    SELECT region FROM sales_summary WHERE total > 1000
`

// Recursive CTE for hierarchical data
sql := `
    WITH RECURSIVE employee_tree AS (
        SELECT employee_id, manager_id, name 
        FROM employees 
        WHERE manager_id IS NULL
        UNION ALL
        SELECT e.employee_id, e.manager_id, e.name 
        FROM employees e 
        JOIN employee_tree et ON e.manager_id = et.employee_id
    ) 
    SELECT * FROM employee_tree
`

// Multiple CTEs in single query
sql := `
    WITH regional AS (SELECT region, total FROM sales),
         summary AS (SELECT region FROM regional WHERE total > 1000)
    SELECT * FROM summary
`

Set Operations

// UNION - combine results with deduplication
sql := "SELECT name FROM users UNION SELECT name FROM customers"

// UNION ALL - combine results preserving duplicates
sql := "SELECT id FROM orders UNION ALL SELECT id FROM invoices"

// EXCEPT - set difference
sql := "SELECT product FROM inventory EXCEPT SELECT product FROM discontinued"

// INTERSECT - set intersection
sql := "SELECT customer_id FROM orders INTERSECT SELECT customer_id FROM payments"

// Left-associative parsing for multiple operations
sql := "SELECT a FROM t1 UNION SELECT b FROM t2 INTERSECT SELECT c FROM t3"
// Parsed as: (SELECT a FROM t1 UNION SELECT b FROM t2) INTERSECT SELECT c FROM t3

Complete JOIN Support

GoSQLX supports all JOIN types with proper left-associative tree logic:

// Complex JOIN query with multiple table relationships
sql := `
    SELECT u.name, o.order_date, p.product_name, c.category_name
    FROM users u
    LEFT JOIN orders o ON u.id = o.user_id  
    INNER JOIN products p ON o.product_id = p.id
    RIGHT JOIN categories c ON p.category_id = c.id
    WHERE u.active = true
    ORDER BY o.order_date DESC
`

// Parse with automatic JOIN tree construction
tkz := tokenizer.GetTokenizer()
defer tokenizer.PutTokenizer(tkz)

tokens, err := tkz.Tokenize([]byte(sql))
parser := parser.NewParser()
ast, err := parser.Parse(tokens)

// Access JOIN information
if selectStmt, ok := ast.Statements[0].(*ast.SelectStatement); ok {
    fmt.Printf("Found %d JOINs:\n", len(selectStmt.Joins))
    for i, join := range selectStmt.Joins {
        fmt.Printf("JOIN %d: %s (left: %s, right: %s)\n", 
            i+1, join.Type, join.Left.Name, join.Right.Name)
    }
}

Supported JOIN Types:

• ✅ INNER JOIN - Standard inner joins
• ✅ LEFT JOIN / LEFT OUTER JOIN - Left outer joins
• ✅ RIGHT JOIN / RIGHT OUTER JOIN - Right outer joins
• ✅ FULL JOIN / FULL OUTER JOIN - Full outer joins
• ✅ CROSS JOIN - Cartesian product joins
• ✅ NATURAL JOIN - Natural joins (implicit ON clause)
• ✅ USING (column) - Single-column using clause

Advanced SQL Features (v1.4+)

MERGE Statements (SQL:2003 F312)

sql := `
    MERGE INTO target_table t
    USING source_table s ON t.id = s.id
    WHEN MATCHED THEN
        UPDATE SET t.name = s.name, t.value = s.value
    WHEN NOT MATCHED THEN
        INSERT (id, name, value) VALUES (s.id, s.name, s.value)
`
ast, err := gosqlx.Parse(sql)

GROUPING SETS, ROLLUP, CUBE (SQL-99 T431)

// GROUPING SETS - explicit grouping combinations
sql := `SELECT region, product, SUM(sales)
        FROM orders
        GROUP BY GROUPING SETS ((region), (product), (region, product), ())`

// ROLLUP - hierarchical subtotals
sql := `SELECT year, quarter, month, SUM(revenue)
        FROM sales
        GROUP BY ROLLUP (year, quarter, month)`

// CUBE - all possible combinations
sql := `SELECT region, product, SUM(amount)
        FROM sales
        GROUP BY CUBE (region, product)`

Materialized Views

// Create materialized view
sql := `CREATE MATERIALIZED VIEW sales_summary AS
        SELECT region, SUM(amount) as total
        FROM sales GROUP BY region`

// Refresh materialized view
sql := `REFRESH MATERIALIZED VIEW CONCURRENTLY sales_summary`

// Drop materialized view
sql := `DROP MATERIALIZED VIEW IF EXISTS sales_summary`

SQL Injection Detection

import "github.com/ajitpratap0/GoSQLX/pkg/sql/security"

// Create scanner
scanner := security.NewScanner()

// Scan for injection patterns
result := scanner.Scan(ast)

if result.HasCritical() {
    fmt.Printf("Found %d critical issues!\n", result.CriticalCount)
    for _, finding := range result.Findings {
        fmt.Printf("  [%s] %s: %s\n",
            finding.Severity, finding.Pattern, finding.Description)
    }
}

// Detected patterns include:
// - Tautology (1=1, 'a'='a')
// - UNION-based injection
// - Time-based blind (SLEEP, WAITFOR DELAY)
// - Comment bypass (--, /**/)
// - Stacked queries
// - Dangerous functions (xp_cmdshell, LOAD_FILE)

Expression Operators (BETWEEN, IN, LIKE, IS NULL)

// BETWEEN with expressions
sql := `SELECT * FROM orders WHERE amount BETWEEN 100 AND 500`

// IN with subquery
sql := `SELECT * FROM users WHERE id IN (SELECT user_id FROM admins)`

// LIKE with pattern matching
sql := `SELECT * FROM products WHERE name LIKE '%widget%'`

// IS NULL / IS NOT NULL
sql := `SELECT * FROM users WHERE deleted_at IS NULL`

// NULLS FIRST/LAST ordering (SQL-99 F851)
sql := `SELECT * FROM users ORDER BY last_login DESC NULLS LAST`

PostgreSQL-Specific Features (v1.6+)

LATERAL JOIN - Correlated subqueries in FROM clause:

// LATERAL allows referencing columns from preceding tables
sql := `
    SELECT u.name, recent_orders.order_date, recent_orders.total
    FROM users u
    LEFT JOIN LATERAL (
        SELECT order_date, total
        FROM orders
        WHERE user_id = u.id
        ORDER BY order_date DESC
        LIMIT 1
    ) AS recent_orders ON true
`
ast, err := gosqlx.Parse(sql)

ORDER BY inside Aggregates - Ordered set functions:

// STRING_AGG with ORDER BY
sql := `SELECT STRING_AGG(name, ', ' ORDER BY name DESC NULLS LAST) FROM users`

// ARRAY_AGG with ORDER BY
sql := `SELECT ARRAY_AGG(value ORDER BY created_at, priority DESC) FROM items`

// JSON_AGG with ORDER BY
sql := `SELECT JSON_AGG(employee_data ORDER BY hire_date) FROM employees`

// Multiple aggregates with different orderings
sql := `
    SELECT
        department,
        STRING_AGG(name, '; ' ORDER BY name ASC NULLS FIRST) AS employee_names,
        ARRAY_AGG(salary ORDER BY salary DESC) AS salaries
    FROM employees
    GROUP BY department
`
ast, err := gosqlx.Parse(sql)

JSON/JSONB Operators - PostgreSQL JSON support:

// Arrow operators for field access
sql := `SELECT data -> 'user' -> 'profile' ->> 'email' FROM users`

// Path operators for nested access
sql := `SELECT data #> '{address,city}', data #>> '{address,zipcode}' FROM users`

// Containment operators
sql := `SELECT * FROM users WHERE data @> '{"active": true}'`
sql := `SELECT * FROM users WHERE '{"admin": true}' <@ data`

// Combined JSON operators in complex queries
sql := `
    SELECT
        u.id,
        u.data ->> 'name' AS user_name,
        u.data -> 'settings' ->> 'theme' AS theme
    FROM users u
    WHERE u.data @> '{"verified": true}'
    AND u.data ->> 'status' = 'active'
`
ast, err := gosqlx.Parse(sql)

DISTINCT ON - PostgreSQL unique row selection:

// Select first row per group based on ordering
sql := `
    SELECT DISTINCT ON (user_id) user_id, created_at, status
    FROM orders
    ORDER BY user_id, created_at DESC
`
ast, err := gosqlx.Parse(sql)

FILTER Clause - Conditional aggregation:

// COUNT with FILTER
sql := `
    SELECT
        COUNT(*) AS total_orders,
        COUNT(*) FILTER (WHERE status = 'completed') AS completed_orders,
        SUM(amount) FILTER (WHERE region = 'US') AS us_revenue
    FROM orders
`
ast, err := gosqlx.Parse(sql)

Examples

Multi-Dialect Support

// PostgreSQL with array operators
sql := `SELECT * FROM users WHERE tags @> ARRAY['admin']`

// MySQL with backticks
sql := "SELECT `user_id`, `name` FROM `users`"

// SQL Server with brackets
sql := "SELECT [user_id], [name] FROM [users]"

Unicode and International SQL

// Japanese
sql := `SELECT "名前", "年齢" FROM "ユーザー"`

// Russian
sql := `SELECT "имя", "возраст" FROM "пользователи"`

// Arabic
sql := `SELECT "الاسم", "العمر" FROM "المستخدمون"`

// Emoji support
sql := `SELECT * FROM users WHERE status = '🚀'`

Concurrent Processing

func ProcessConcurrently(queries []string) {
    var wg sync.WaitGroup
    
    for _, sql := range queries {
        wg.Add(1)
        go func(query string) {
            defer wg.Done()
            
            // Each goroutine gets its own tokenizer
            tkz := tokenizer.GetTokenizer()
            defer tokenizer.PutTokenizer(tkz)
            
            tokens, _ := tkz.Tokenize([]byte(query))
            // Process tokens...
        }(sql)
    }
    
    wg.Wait()
}

Performance

v1.0.0 Performance Improvements

Metric	Previous	v1.0.0	Improvement
Sustained Throughput	2.2M ops/s	946K+ ops/s	Production Grade ✅
Peak Throughput	2.2M ops/s	1.25M+ ops/s	Enhanced ✅
Token Processing	8M tokens/s	8M+ tokens/s	Maintained ✅
Simple Query Latency	200ns	<280ns	Optimized ✅
Complex Query Latency	N/A	<1μs (CTE/Set Ops)	New Capability ✅
Memory Usage	Baseline	60-80% reduction	-70% ✅
SQL-92 Compliance	40%	~70%	+75% ✅

Latest Benchmark Results

BenchmarkParserSustainedLoad-16           946,583      1,057 ns/op     1,847 B/op      23 allocs/op
BenchmarkParserThroughput-16            1,252,833        798 ns/op     1,452 B/op      18 allocs/op
BenchmarkParserSimpleSelect-16          3,571,428        279 ns/op       536 B/op       9 allocs/op
BenchmarkParserComplexSelect-16           985,221      1,014 ns/op     2,184 B/op      31 allocs/op

BenchmarkCTE/SimpleCTE-16                 524,933      1,891 ns/op     3,847 B/op      52 allocs/op
BenchmarkCTE/RecursiveCTE-16              387,654      2,735 ns/op     5,293 B/op      71 allocs/op
BenchmarkSetOperations/UNION-16           445,782      2,234 ns/op     4,156 B/op      58 allocs/op

BenchmarkTokensPerSecond-16               815,439      1,378 ns/op   8,847,625 tokens/sec

Performance Characteristics

Metric	Value	Details
Sustained Throughput	946K+ ops/sec	30s load testing
Peak Throughput	1.25M+ ops/sec	Concurrent goroutines
Token Rate	8M+ tokens/sec	Sustained processing
Simple Query Latency	<280ns	Basic SELECT (p50)
Complex Query Latency	<1μs	CTEs/Set Operations
Memory	1.8KB/query	Complex SQL with pooling
Scaling	Linear to 128+	Perfect concurrency
Pool Efficiency	95%+ hit rate	Effective reuse

Run go test -bench=. -benchmem ./pkg/... for detailed performance analysis.

Testing

# Run all tests with race detection
go test -race ./...

# Run benchmarks
go test -bench=. -benchmem ./...

# Generate coverage report
go test -coverprofile=coverage.out ./...
go tool cover -html=coverage.out

# Run specific test suites
go test -v ./pkg/sql/tokenizer/
go test -v ./pkg/sql/parser/

Project Structure

GoSQLX/
├── pkg/
│   ├── models/              # Core data structures
│   │   ├── token.go        # Token definitions
│   │   └── location.go     # Position tracking
│   └── sql/
│       ├── tokenizer/       # Lexical analysis
│       │   ├── tokenizer.go
│       │   └── pool.go
│       ├── parser/          # Syntax analysis
│       │   ├── parser.go
│       │   └── expressions.go
│       ├── ast/            # Abstract syntax tree
│       │   ├── nodes.go
│       │   └── statements.go
│       └── keywords/        # SQL keywords
├── examples/               # Usage examples
│   └── cmd/
│       ├── example.go
│       └── example_test.go
├── docs/                   # Documentation
│   ├── API_REFERENCE.md
│   ├── USAGE_GUIDE.md
│   ├── ARCHITECTURE.md
│   └── TROUBLESHOOTING.md
└── tools/                  # Development tools

Development

Prerequisites

• Go 1.24+
• Task - task runner (install: go install github.com/go-task/task/v3/cmd/task@latest)
• golangci-lint, staticcheck (for code quality, install: task deps:tools)

Task Runner

This project uses Task as the task runner. Install with:

go install github.com/go-task/task/v3/cmd/task@latest
# Or: brew install go-task (macOS)

Building

# Show all available tasks
task

# Build the project
task build

# Build the CLI binary
task build:cli

# Install CLI globally
task install

# Run all quality checks
task quality

# Run all tests
task test

# Run tests with race detection (recommended)
task test:race

# Clean build artifacts
task clean

Code Quality

# Format code
task fmt

# Run go vet
task vet

# Run golangci-lint
task lint

# Run all quality checks (fmt, vet, lint)
task quality

# Full CI check (format, vet, lint, test:race)
task check

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

How to Contribute

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Write tests for new features
• Ensure all tests pass with race detection
• Follow Go idioms and best practices
• Update documentation for API changes
• Add benchmarks for performance-critical code

Roadmap

Phase	Version	Status	Highlights
Phase 1	v1.1.0	✅ Complete	JOIN Support
Phase 2	v1.2.0	✅ Complete	CTEs & Set Operations
Phase 2.5	v1.3.0-v1.4.0	✅ Complete	Window Functions, MERGE, Grouping Sets
Phase 3	v1.5.0-v1.6.0	✅ Complete	PostgreSQL Extensions, LSP, Linter
Phase 4	v1.7.0	🚧 In Progress	MySQL & SQL Server Dialects
Phase 5	v2.0.0	📋 Planned	Query Intelligence & Optimization
Phase 6	v2.1.0	📋 Planned	Schema Awareness & Validation

Phase 1: Core SQL Enhancements - v1.1.0 ✅

• ✅ Complete JOIN support (INNER/LEFT/RIGHT/FULL OUTER/CROSS/NATURAL)
• ✅ Proper join tree logic with left-associative relationships
• ✅ USING clause parsing for single and multi-column joins
• ✅ Enhanced error handling with contextual JOIN error messages
• ✅ Comprehensive test coverage (15+ JOIN scenarios)

Phase 2: CTE & Set Operations - v1.2.0 ✅

• ✅ Common Table Expressions (CTEs) with RECURSIVE support
• ✅ Set operations (UNION/EXCEPT/INTERSECT with ALL modifier)
• ✅ Left-associative set operation parsing
• ✅ CTE column specifications and multiple CTE definitions
• ✅ ~70% SQL-92 compliance achieved

Phase 2.5: Window Functions & Advanced SQL - v1.3.0-v1.4.0 ✅

• ✅ Window Functions - Complete SQL-99 support (ROW_NUMBER, RANK, DENSE_RANK, NTILE, LAG, LEAD, FIRST_VALUE, LAST_VALUE)
• ✅ Window Frames - ROWS/RANGE with PRECEDING/FOLLOWING/CURRENT ROW
• ✅ MERGE Statements - SQL:2003 F312 with WHEN MATCHED/NOT MATCHED clauses
• ✅ GROUPING SETS, ROLLUP, CUBE - SQL-99 T431 advanced grouping
• ✅ Materialized Views - CREATE, REFRESH, DROP support
• ✅ Expression Operators - BETWEEN, IN, LIKE, IS NULL, NULLS FIRST/LAST
• ✅ ~75% SQL-99 compliance achieved

Phase 3: PostgreSQL Extensions & Developer Tools - v1.5.0-v1.6.0 ✅

• ✅ LATERAL JOIN - Correlated subqueries in FROM clause
• ✅ JSON/JSONB Operators - All 10 operators (->, ->>, #>, #>>, @>, <@, ?, ?|, ?&, #-)
• ✅ DISTINCT ON - PostgreSQL-specific row selection
• ✅ FILTER Clause - Conditional aggregation (SQL:2003 T612)
• ✅ Aggregate ORDER BY - ORDER BY inside STRING_AGG, ARRAY_AGG, etc.
• ✅ RETURNING Clause - Return modified rows from INSERT/UPDATE/DELETE
• ✅ LSP Server - Full Language Server Protocol with diagnostics, completion, hover, formatting
• ✅ Linter Engine - 10 built-in rules (L001-L010) with auto-fix
• ✅ Security Scanner - SQL injection detection with severity classification
• ✅ Structured Errors - Error codes E1001-E3004 with position tracking
• ✅ CLI Enhancements - Pipeline support, stdin detection, cross-platform
• ✅ ~80-85% SQL-99 compliance achieved

Phase 4: MySQL & SQL Server Dialects - v1.7.0 🚧

• 🚧 MySQL Extensions - AUTO_INCREMENT, REPLACE INTO, ON DUPLICATE KEY
• 📋 MySQL Functions - DATE_FORMAT, IFNULL, GROUP_CONCAT specifics
• 📋 SQL Server T-SQL - TOP, OFFSET-FETCH, OUTPUT clause
• 📋 SQL Server Functions - ISNULL, CONVERT, DATEPART specifics
• 📋 Dialect Auto-Detection - Automatic syntax detection from queries
• 📋 Cross-Dialect Translation - Convert between dialect syntaxes

Phase 5: Query Intelligence & Optimization - v2.0.0 📋

• 📋 Query Cost Estimation - Complexity analysis and scoring
• 📋 Index Recommendations - Suggest indexes based on query patterns
• 📋 Join Order Optimization - Recommend optimal join sequences
• 📋 Subquery Optimization - Detect and suggest subquery improvements
• 📋 N+1 Query Detection - Identify inefficient query patterns
• 📋 Performance Hints - Actionable optimization suggestions

Phase 6: Schema Awareness & Validation - v2.1.0 📋

• 📋 Schema Definition Parsing - Full DDL understanding
• 📋 Type Checking - Validate column types in expressions
• 📋 Foreign Key Validation - Verify relationship integrity
• 📋 Constraint Checking - NOT NULL, UNIQUE, CHECK validation
• 📋 Schema Diff - Compare and generate migration scripts
• 📋 Entity-Relationship Extraction - Generate ER diagrams from DDL

Future Considerations 🔮

• 📋 Stored Procedures - CREATE PROCEDURE/FUNCTION parsing
• 📋 Triggers - CREATE TRIGGER support
• 📋 PL/pgSQL - PostgreSQL procedural language
• 📋 Query Rewriting - Automatic query transformation
• 📋 WASM Support - Browser-based SQL parsing

See ARCHITECTURE.md for detailed system design and CHANGELOG.md for version history

Community & Support

Join Our Community

Get Help

Channel	Purpose	Response Time
🐛 Bug Reports	Report issues	Community-driven
💡 Feature Requests	Suggest improvements	Community-driven
💬 Discussions	Q&A, ideas, showcase	Community-driven
🔒 Security	Report vulnerabilities	Best effort

Contributors

Core Team

How to Contribute

We love your input! We want to make contributing as easy and transparent as possible.

Quick Contribution Guide

1. 🍴 Fork the repo
2. 🔨 Make your changes
3. ✅ Ensure tests pass (go test -race ./...)
4. 📝 Update documentation
5. 🚀 Submit a PR

Use Cases

Industry	Use Case	Benefits
🏦 FinTech	SQL validation & auditing	Fast validation, compliance tracking
📊 Analytics	Query parsing & optimization	Real-time analysis, performance insights
🛡️ Security	SQL injection detection	Pattern matching, threat prevention
🏗️ DevTools	IDE integration & linting	Syntax highlighting, auto-completion
📚 Education	SQL learning platforms	Interactive parsing, error explanation
🔄 Migration	Cross-database migration	Dialect conversion, compatibility check

Who's Using GoSQLX

Using GoSQLX in production? Let us know!

Project Metrics

Performance Benchmarks

graph LR
    A[SQL Input] -->|946K+ ops/sec| B[Tokenizer]
    B -->|8M+ tokens/sec| C[Parser]
    C -->|Zero-copy| D[AST]
    D -->|60-80% less memory| E[Output]

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Other Ways to Support

• ⭐ Star this repository
• 🐦 Tweet about GoSQLX
• 📝 Write a blog post
• 🎥 Create a tutorial
• 🐛 Report bugs
• 💡 Suggest features
• 🔧 Submit PRs

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0) - see the LICENSE file for details.

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