Introduction
CoinExchange is a fully open-source cryptocurrency exchange platform featuring:
- Complete Java-based matching engine
- Multi-platform support (Web, Android, iOS)
- Comprehensive wallet RPC integration
- Microservice architecture for scalability
Legal Note: This project is intended for educational purposes only. Commercial use requires proper licensing.
Key Technical Features
- In-Memory Matching Engine
Processes orders 10-20x faster than traditional database-based solutions. API-First Architecture
- JWT token authentication
- RESTful interfaces for all trading functions
Microservice Components:
| Service | Functionality | |-------------------|-----------------------------------| | cloud.jar | Service registry | | match-engine.jar | Order matching | | market.jar | Real-time price feeds | | user-center.jar | Account management |High-Performance Stack:
- Kafka message queues
- Redis caching
- MySQL/NoSQL hybrid storage
Deployment Guide
Prerequisites
- MySQL 5.5+ (
xxxxdatabase) - Redis 3.2+
- Kafka 2.2+
- Java 8 JDK
- Nginx (production)
Configuration Steps
Set environment variables:
# Database spring.datasource.url=jdbc:mysql://localhost:3306/xxxx spring.datasource.username=admin spring.datasource.password=[your_password] # Redis spring.redis.host=127.0.0.1Initialize services in order:
java -jar cloud.jar # Registry java -jar match-engine.jar # Core engine java -jar market.jar # Market data- Deploy frontend Vue projects separately.
Core Functionality
User Features
- Multi-factor authentication
- Spot trading (limit/market orders)
- OTC/C2C fiat gateways
- Referral programs
- Asset management dashboard
Admin Features
- Real-time monitoring
- User balance adjustments
- Trading pair management
- Automated market making bots
FAQ
Q: Is cold wallet storage supported?
A: Yes, the system implements segregated cold/hot wallets with multi-signature withdrawals.
Q: What cryptocurrencies are pre-configured?
A: BTC, ETH, USDT with complete RPC interfaces. Additional coins can be added via admin panel.
Q: How to handle high traffic loads?
A: The Kafka-based architecture allows horizontal scaling - simply deploy additional matching engine instances.
Optimization Tips
- Use SSDs for Redis persistence
- Configure Kafka replication factor ≥3 in production
- Monitor JVM heap size for matching engine
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Disclaimer: This documentation represents technical capabilities only. Actual implementation may vary based on customization.