📈 Track and visualize real-time crypto orderbooks across multiple exchanges with a Go backend and React frontend for seamless access and insights.
Locally runnable server with built-in data caching, providing both tick-level historical and consolidated real-time cryptocurrency market data via HTTP and WebSocket APIs
Convenient access to tick-level real-time and historical cryptocurrency market data via Node.js
The most largest prediction market - Polymarket copy trading bot: Copy master's trades and positions by using this bot
Open source software that helps you create and deploy high-frequency crypto trading bots
Exchange Starter Kit to run your own Digital Asset Trading Exchange Platform
polymarket spike trading bot, orderbook monitoring, spike trading
CCXT.SIMPLE – CryptoCurrency eXchange Trading Library Simple, Modern .NET cryptocurrency trading library - Unified API access to 110 exchange adapters (8 FULL, 3 PARTIAL, 99 SKELETON) with a focus on simplicity and performance.
CCXT.COLLECT – CryptoCurrency eXchange Trading Collector, A powerful .NET library for real-time cryptocurrency exchange data collection with unified WebSocket streaming and technical indicator analysis.
Real-time crypto order book heatmap with quant metrics. Multi-exchange: Binance, OKX, Bybit. Index α, CVD, Delta visualization.
Decentralized NFT marketplace with EIP-712 signed listings, royalty support and platform fees
A modular, high-performance cryptocurrency exchange platform built with Rust
A provable orderbook based on Hyli.
Free, open source, a high frequency trading and market making backtesting and trading bot, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books(Level-2 and Level-3), with real-world crypto trading examples for Binance and Bybit
A high-performance, concurrent Limit Order Book (LOB) and Matching Engine written in Go. Designed for low-latency trading simulations using price-time priority.
Real-time Orderbook Data Pipeline (Kafka, Python, Docker). This project demonstrates a production-inspired real-time data pipeline for market/trading data. It simulates high-frequency orderbook ticks, publishes them to Kafka, and verifies durable ingestion using containerized infrastructure.
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