⚡ Exchange Platform

DEPLOYED LINK - https://exchange-ruby-iota.vercel.app

A high-performance, real-time trading system built to handle low-latency order execution at scale. The platform combines modular, event-driven architecture with efficient queuing, real-time communication, and scalable infrastructure.

🚀 Tech Stack

Frontend

• Next.js & React – Dynamic, server-rendered UI
• Tailwind CSS – Fast, responsive styling

Backend

• Node.js & Express – High-performance API services
• PostgreSQL – Transactional data storage
• Time Series DB – For high-frequency trade analytics

Real-Time Communication

• WebSockets (Socket.io) – Live trade and market updates

Queue & Event System

• Redis – Order queuing, Pub/Sub for real-time communication

Matching Engine

• Custom-built in Node.js – Fast order matching with event triggers

Deployment

• Railway – Cloud deployment

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🧠 Architecture & Data Flow

1. Order Submission

• User Input: Traders place buy/sell orders via the frontend.
• API Request: Order data is sent to POST /api/v1/order.
• Redis Queue: API validates and enqueues orders for processing.

2. Order Matching

• Engine Polling: A custom-built matching engine polls Redis.
• Execution: Orders are matched and trades executed.
• Event Trigger: Emits a trade_created event via Redis Pub/Sub.

3. Real-Time Distribution & Storage

• WebSockets: Broadcast updates to connected clients instantly.
• PostgreSQL: Stores all trade records reliably.
• Time Series DB: Logs price/volume data for analytics and visualization.

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✨ Key Features

• ⚡ Real-Time Execution – Millisecond-level trade processing
• 📈 Live Market Updates – Instant updates via WebSockets
• 🔁 Scalable Design – Horizontally scalable with decoupled services
• 🧮 Efficient Storage – Dual-database approach for speed and analytics

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🧩 Challenges & Solutions

Handling High Throughput

• Problem: Concurrent order spikes
• Solution: Redis queue decouples order intake from processing

Ensuring Real-Time Execution

• Problem: Trade delay risks
• Solution: Optimized matching engine + Redis Pub/Sub + WebSockets

Efficient Data Persistence

• Problem: High-frequency data impacting performance
• Solution: PostgreSQL for core trades, Time Series DB for analytics

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📦 Setup Instructions

# 1. Clone the repo
git clone https://github.com/yourusername/exchange-platform.git
cd exchange-platform

# 2. Install dependencies
npm install

# 3. Setup environment variables
cp .env.example .env

# 4. Start the dev server
npm run dev