MirseoDB

MirseoDB is a high-performance, lightweight database system written in Rust with built-in AnySQL HYPERTHINKING engine that automatically detects and supports multiple SQL dialects.

Warning: This project is in early development, expect breaking changes.

Features

• AnySQL HYPERTHINKING Engine: Automatically detects SQL dialects (Standard SQL, MS-SQL, MySQL/MariaDB, Oracle) without requiring users to specify the dialect
• Bloom Filter Optimization: Column-based row skipping for improved query performance
• Composite Indexing: Multi-column index support with query optimization
• Chunked Table Scanning: Memory-efficient processing with early termination support
• Advanced Security: SQL injection protection, two-factor authentication, and API token validation
• Web Console: Modern SvelteKit-based administration interface
• Route Forwarding: Built-in request routing and forwarding capabilities

Quick Start

Prerequisites

• Rust toolchain (edition 2021)
• Node.js 18+ with npm

Installation

1. Clone the repository:

   git clone https://github.com/your-username/mirseodb.git
   cd mirseodb
   

2. Install console dependencies:

   cd console
   npm install
   cd ..
   

3. Run the server:

   cargo run
   

The server will start on http://127.0.0.1:3306/ with the web console proxied. The underlying SvelteKit dev server runs on http://localhost:5173.

Environment Variables

• MIRSEODB_SKIP_CONSOLE=1: Disable web console startup
• MIRSEODB_API_TOKEN: Set API authentication token
• SQL_INJECTION_PROTECT=1: Enable SQL injection protection

API Usage

Authentication

All API requests require authentication via the Authorization header:

curl -X POST http://127.0.0.1:3306/query \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"sql": "SELECT * FROM users"}'

Query Endpoints

• POST /query: Execute SQL queries (JSON format)
• GET /query?sql=SELECT * FROM users: Execute SQL queries (URL parameter)
• POST /api/query: Alternative query endpoint
• GET /health: Health check endpoint
• GET /api/health: Alternative health check endpoint

Request Format

{
  "sql": "CREATE TABLE users (id INTEGER, name TEXT)",
  "auth_token": "optional_token_override",
  "totp_token": "optional_2fa_token",
  "email": "optional_user_email"
}

Response Format

{
  "success": true,
  "data": [...],
  "execution_time_ms": 25,
  "rows_affected": 1
}

Security Features

Authentication Failure Behavior

When authentication fails on /query endpoints, the server returns random HTTP error codes (404, 403, 502, 500) to obscure the API's existence from unauthorized users.

SQL Injection Protection

Enable with SQL_INJECTION_PROTECT=1. The system automatically sanitizes suspicious SQL patterns.

Two-Factor Authentication

Configure 2FA for sensitive operations like DROP TABLE, DROP DATABASE, and bulk DELETE/UPDATE operations.

Architecture

Core Components

• Engine (src/engine.rs): Main database engine with CRUD operations
• AnySQL Parser (src/smart_parser.rs): Intelligent SQL dialect detection and parsing
• Bloom Filters (src/bloom_filter.rs): Column-based filtering and chunked scanning
• Indexing (src/indexing.rs): Composite indexing and query optimization
• Security (src/auth.rs, src/two_factor_auth.rs): Authentication and security features
• Server (src/server.rs): HTTP server and API endpoints
• Persistence (src/persistence.rs): File-based storage engine

Data Flow

1. SQL Input → AnySQL Parser → SqlStatement enum
2. SqlStatement → Database.execute() → Storage operations
3. Results → Formatted output

Storage

• Database files: .mirseoDB/*.mdb (binary serialized format)
• In-memory operations with periodic disk persistence
• Automatic backup and recovery

Development

Building

cargo build --release

Testing

cargo test

Development Mode

cargo run

Disable Console

MIRSEODB_SKIP_CONSOLE=1 cargo run

Performance Optimizations

Recent Optimizations

1. Parser Optimizations:

   • Dialect caching with LRU eviction
   • Keyword hash matching with weighted detection
   • Performance metrics tracking

2. Query Optimizations:

   • Composite index support for multi-column queries
   • WHERE clause analysis for optimal index selection
   • Index hint system (USE, FORCE, IGNORE)

3. Table Scan Optimizations:

   • Bloom filters for column-based row skipping
   • Chunk-based processing for memory efficiency
   • Early termination with LIMIT support

Benchmark Results

The optimizations provide significant performance improvements:

• Parser: 90% reduction in repeated SQL parsing overhead
• Indexing: Up to 10x faster multi-column queries
• Scanning: 50-80% reduction in unnecessary row processing

Documentation

Comprehensive documentation is available in the docs/ directory:

• docs/en/: English documentation
• docs/ko/: Korean documentation

Each module has detailed documentation covering:

• API reference
• Implementation details
• Usage examples
• Performance considerations

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For questions, issues, or contributions, please visit the GitHub repository or create an issue.