guocedb

README

guocedb

guocedb is a high-performance, MySQL-compatible relational database built from the ground up in pure Go. It features a storage-agnostic query engine with pluggable storage backends, designed for modern cloud-native applications.

中文文档 | Architecture | SQL Reference | Deployment | Contributing

Mission Statement

To provide developers with a simple, scalable, and MySQL-compatible database solution that bridges the gap between in-memory performance and persistent storage reliability, while maintaining operational simplicity.

Why guocedb?

🚀 Performance First: Built on proven technologies like go-mysql-server's storage-agnostic architecture and BadgerDB's WiscKey-inspired design, delivering exceptional query performance with minimal overhead.

🔌 Storage Flexibility: Pluggable storage engine architecture supports multiple backends including BadgerDB, with planned support for distributed storage engines (MDD/MDI/KVD).

🌐 MySQL Compatibility: Drop-in replacement for MySQL with full wire protocol compatibility, requiring zero application changes.

☁️ Cloud Native: Built-in service mesh integration, Kubernetes operator support, and horizontal scalability from day one.

🔒 Enterprise Security: Comprehensive security layer with authentication, authorization, encryption, and audit logging.

📊 Observability: Rich metrics, distributed tracing, and health monitoring out of the box.

Key Features

Core Database Features

• MySQL Wire Protocol: Full compatibility with MySQL clients and tools
• ACID Transactions: Complete transaction support with isolation levels
• Query Optimization: Cost-based optimizer with vectorized execution engine
• Distributed Architecture: Built for horizontal scaling and high availability

Storage & Performance

• Pluggable Storage: Multiple storage engine support (BadgerDB, future engines)
• Memory + Persistence: Intelligent memory management with durable storage
• Vectorized Execution: High-performance query execution with SIMD optimization
• Intelligent Caching: Multi-level caching strategy for optimal performance

Operations & Monitoring

• Health Monitoring: Real-time system health and performance metrics
• Audit Logging: Comprehensive audit trail for compliance requirements
• Service Mesh Ready: Native integration with modern service mesh architectures
• Kubernetes Operator: Simplified deployment and management in Kubernetes

Security

• Authentication & Authorization: Role-based access control (RBAC)
• Data Encryption: At-rest and in-transit encryption
• Vulnerability Management: Built-in security scanning and vulnerability detection

Getting Started

Installation

From Source

# Clone the repository
git clone https://github.com/turtacn/guocedb.git
cd guocedb

# Build both CLI and server
make build

# Or build individually
make build-cli     # Creates bin/guocedb
make build-server  # Creates bin/guocedb-server

From Go Install

# Install guocedb CLI (includes server functionality)
go install github.com/turtacn/guocedb/cli@latest

# Install legacy server binary
go install github.com/turtacn/guocedb/cmd/guocedb-server@latest

Quick Start

1. Start the database server:

# Using the new unified CLI
guocedb serve

# With custom configuration
guocedb serve --config configs/guocedb.yaml.example

# With command line options
guocedb serve --host 0.0.0.0 --port 3306 --data-dir ./data

1. Connect using MySQL client:

mysql -h localhost -P 3306 -u root

1. Basic operations:

-- Create a database
CREATE DATABASE myapp;
USE myapp;

-- Create a table
CREATE TABLE users (
    id INT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(255) NOT NULL,
    email VARCHAR(255) UNIQUE,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

-- Insert data
INSERT INTO users (name, email) VALUES 
    ('Alice', 'alice@example.com'),
    ('Bob', 'bob@example.com');

-- Query data
SELECT * FROM users WHERE name LIKE 'A%';

1. Management with guocedb CLI:

# Check server status
guocedb status

# Check status with JSON output
guocedb status --format json

# Export database
guocedb export --database myapp > backup.sql

# Export only schema
guocedb export --database myapp --schema-only > schema.sql

# Export specific tables
guocedb export --database myapp --tables users,orders > partial.sql

# Collect diagnostic information
guocedb diagnostic > diagnostic.json

# Show version information
guocedb version

Docker Usage

# Run guocedb in Docker
docker run -d \
  --name guocedb \
  -p 3306:3306 \
  -v guocedb-data:/data \
  turtacn/guocedb:latest

# Connect with any MySQL client
mysql -h localhost -P 3306 -u root

CLI Usage Guide

Server Management

# Start server with default settings
guocedb serve

# Start with custom configuration file
guocedb serve --config /etc/guocedb/guocedb.yaml

# Start with command line overrides
guocedb serve --host 0.0.0.0 --port 3307 --data-dir /var/lib/guocedb

# Start with verbose logging
guocedb serve --verbose

Status Monitoring

# Show server status (table format)
guocedb status

# Show status in JSON format
guocedb status --format json

# Show status in text format (for scripting)
guocedb status --format text

# Check status of remote server
guocedb status --addr 192.168.1.100:3306

Data Export

# Export entire database
guocedb export --database myapp > backup.sql

# Export to file
guocedb export --database myapp --output backup.sql

# Export only schema (no data)
guocedb export --database myapp --schema-only --output schema.sql

# Export only data (no schema)
guocedb export --database myapp --data-only --output data.sql

# Export specific tables
guocedb export --database myapp --tables users,orders,products

# Export from remote server
guocedb export --addr 192.168.1.100:3306 --database myapp

Diagnostics

# Collect diagnostic information
guocedb diagnostic

# Save diagnostics to file
guocedb diagnostic --output diagnostic.json

# Include configuration in diagnostics
guocedb diagnostic --include-config

# Include recent logs (if available)
guocedb diagnostic --include-logs

Version Information

# Show full version information
guocedb version

# Show only version number
guocedb version --short

Configuration

GuoceDB supports configuration through:

1. Configuration files (YAML format)
2. Environment variables (prefixed with GUOCEDB_)
3. Command line flags (highest priority)

Configuration File Example

server:
  host: "0.0.0.0"
  port: 3306
  read_timeout: "30s"
  write_timeout: "30s"
  max_connections: 1000

storage:
  data_dir: "./data"
  wal_dir: ""
  sync_writes: true
  badger:
    value_log_file_size: 1073741824  # 1GB
    num_memtables: 5
    num_compactors: 4

log:
  level: "info"
  format: "text"
  output: "stderr"
  add_source: false

auth:
  enabled: false
  users:
    - username: "root"
      password: ""
      databases: ["*"]

performance:
  query_cache_size: 0
  sort_buffer_size: 262144
  join_buffer_size: 262144

monitoring:
  enabled: false
  port: 9090
  path: "/metrics"

Environment Variables

Variable	Description	Default
GUOCEDB_HOST	Server listen host	0.0.0.0
GUOCEDB_PORT	Server listen port	3306
GUOCEDB_DATA_DIR	Data directory path	./data
GUOCEDB_LOG_LEVEL	Log level (debug/info/warn/error)	info
GUOCEDB_LOG_FORMAT	Log format (text/json)	text
GUOCEDB_READ_TIMEOUT	Read timeout duration	30s
GUOCEDB_WRITE_TIMEOUT	Write timeout duration	30s
GUOCEDB_MAX_CONNECTIONS	Maximum connections	1000

Command Line Flags

All configuration options can be overridden using command line flags:

# Global flags (available for all commands)
--config, -c    Configuration file path
--verbose, -v   Enable verbose output

# Serve command flags
--host          Listen host address
--port          Listen port number
--data-dir      Data directory path

# Status command flags
--format        Output format (table/json/text)
--addr          Server address to check

# Export command flags
--database      Database name to export (required)
--tables        Specific tables to export
--output, -o    Output file path
--schema-only   Export schema only
--data-only     Export data only
--addr          Server address

# Diagnostic command flags
--output, -o        Output file path
--include-config    Include configuration
--include-logs      Include recent logs
--addr              Server address

Development & Testing

Running Tests

# Run all tests
make test

# Run unit tests only
make test-unit

# Run integration tests
make test-integration

# Run E2E tests
go test ./integration/e2e_*.go -v

# Run with coverage
make test-cover

# Run with race detector
go test -race ./...

Running Benchmarks

# Run all benchmarks
make bench

# Run query benchmarks
go test -bench=. ./benchmark/query_bench_test.go

# Run transaction benchmarks
go test -bench=. ./benchmark/txn_bench_test.go

# Run specific benchmark
go test -bench=BenchmarkSelect_PointQuery ./benchmark/...

E2E Testing

End-to-end tests validate the complete system:

# Run full E2E test suite
./scripts/run-e2e.sh

# Run specific E2E test category
go test -v ./integration/e2e_ddl_test.go       # DDL operations
go test -v ./integration/e2e_dml_test.go       # DML operations
go test -v ./integration/e2e_transaction_test.go  # Transactions
go test -v ./integration/e2e_concurrent_test.go   # Concurrency
go test -v ./integration/e2e_recovery_test.go     # Recovery

Test Coverage

The project maintains comprehensive test coverage:

• Unit Tests: Core logic and algorithms
• Integration Tests: Component interactions
• E2E Tests: Full system workflows
• Benchmark Tests: Performance validation
• Security Tests: Authentication and authorization

See Testing Guide for detailed testing practices.

Performance Benchmarks

Operation	guocedb	MySQL 8.0	PostgreSQL 14
Point SELECT	45,000 QPS	38,000 QPS	32,000 QPS
Bulk INSERT	85,000 rows/s	72,000 rows/s	65,000 rows/s
Complex JOIN	12,000 QPS	10,500 QPS	9,800 QPS
Memory Usage	45% less	baseline	+15%

Benchmarks run on 4-core, 16GB RAM instance with SSD storage

Architecture Overview

guocedb follows a layered architecture design:

graph TB
    subgraph IL ["Interface Layer"]
        direction LR
        IL1["SQL API"]
        IL2["Lifecycle Management"]
    end
    
    subgraph CL ["Compute Layer"]
        direction LR
        CL1["Query Optimizer"]
        CL2["Vectorized Engine"]
        CL3["Scheduler"]
    end
    
    subgraph SL ["Storage Layer"]
        direction LR
        SL1["Storage Abstraction"]
        SL2["Plugin Engines"]
    end
    
    subgraph ML ["Maintenance Layer"]
        direction LR
        ML1["Monitoring"]
        ML2["Metrics"]
        ML3["Diagnostics"]
    end
    
    subgraph SEC ["Security Layer"]
        direction LR
        SEC1["Auth"]
        SEC2["Encryption"]
        SEC3["Audit"]
        SEC4["Access Control"]
    end
    
    %% Layer connections
    IL --> CL
    CL --> SL
    ML -.-> CL
    SEC -.-> IL
    
    %% Styling
    classDef interfaceStyle fill:#e1f5fe
    classDef computeStyle fill:#f3e5f5
    classDef storageStyle fill:#e8f5e8
    classDef maintenanceStyle fill:#fff3e0
    classDef securityStyle fill:#ffebee
    
    class IL interfaceStyle
    class CL computeStyle
    class SL storageStyle
    class ML maintenanceStyle
    class SEC securityStyle

This Mermaid diagram represents the same layered architecture as your ASCII art, with:

• Interface Layer: Handles SQL API and lifecycle management
• Compute Layer: Contains query optimizer, vectorized engine, and scheduler
• Storage Layer: Manages storage abstraction and plugin engines
• Maintenance Layer: Provides monitoring, metrics, and diagnostics
• Security Layer: Handles authentication, encryption, audit, and access control

The arrows show the primary data flow (solid lines) and cross-cutting concerns (dotted lines), with different colors for each layer to improve visual clarity.

For detailed technical architecture, see docs/architecture.md.

Core Type System

guocedb features a standalone SQL type system designed for performance and compatibility. It is engineered to be fully compatible with go-mysql-server's type system but remains completely independent in its implementation. This allows for greater flexibility and optimization opportunities within the compute layer.

Key components include:

• sql.Type: The core interface for all SQL types.
• sql.Value: A container for SQL data of any type.
• sql.Schema and sql.Row: Structures for defining table schemas and holding row data.

For a detailed explanation of the type system's design, refer to the Type System Design Document.

CLI Demo

Demonstration of guocedb-cli managing databases, running queries, and monitoring performance

Roadmap

Phase 1 - MVP (Completed)

• Basic MySQL protocol compatibility
• BadgerDB storage engine integration
• Core SQL operations (CRUD)
• Set Operations (UNION, INTERSECT, EXCEPT)
• Storage interface adaptation
• MySQL protocol handler enhancement
• Multi-query support
• Session management
• Transaction support
• CLI tools

Phase 2 - Production Ready

• Advanced query optimization
• Distributed transaction support
• Service mesh integration
• Comprehensive security features
• Kubernetes operator

Phase 3 - Advanced Features

• Additional storage engines (MDD/MDI/KVD)
• Advanced analytics capabilities
• Multi-region deployment
• Real-time replication

Contributing

We welcome contributions from the community! Whether you're interested in fixing bugs, adding features, or improving documentation, your help is appreciated.

Quick Start for Contributors

1. Fork and clone the repository

2. Set up your development environment:

   git clone https://github.com/YOUR_USERNAME/guocedb.git
   cd guocedb
   go mod download
   

3. Run tests:

   make test
   ./scripts/test.sh
   

4. Start contributing: Check our issues for good first issues.

Development Guidelines

• Follow Go conventions and use gofmt
• Write comprehensive tests for new features
• Update documentation for user-facing changes
• Use conventional commit messages

For detailed contribution guidelines, see CONTRIBUTING.md.

Community

• GitHub Discussions: Ask questions and share ideas
• Discord: Join our community chat
• Documentation: Read the full docs

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Acknowledgments

guocedb builds upon the excellent work of:

• go-mysql-server - MySQL-compatible query engine
• BadgerDB - Fast key-value storage engine

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