How to Handle High-Frequency Trading (HFT) Efficiently in a Centralized Crypto Exchange?

Problem-
High-frequency trading (HFT) requires processing a large number of orders per second. Many exchanges struggle with performance bottlenecks in their order matching engine (OME) due to poor WebSocket handling or inefficient database transactions.

Solution-
Use WebSockets instead of HTTP polling for real-time updates and optimize your order matching engine using an in-memory database like Redis.

Example Implementation in Node.js-
javascript

const WebSocket = require('ws');
const wss = new WebSocket.Server({ port: 8080 });

wss.on('connection', (ws) => {
    console.log('Client connected');
    ws.on('message', (message) => {
        console.log(`Received: ${message}`);
        ws.send(`Order received: ${message}`);
    });
});

This ensures low-latency order processing. Additionally, use multi-threading (worker threads) and queue-based processing (RabbitMQ/Kafka) for scaling.

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