AllTick API

AllTick API is a unified high-performance, ultra-low latency full-market real-time and historical market data interface designed for developers and quantitative traders, supporting both WebSocket and REST. It covers A-shares, US stocks, Hong Kong stocks, major market indices, forex, cryptocurrencies, precious metals such as gold and silver, and other commodities.

Official Website: https://alltick.co/

API Documentation: https://apis.alltick.co/

GitHub: https://github.com/alltick/alltick-realtime-forex-crypto-stock-tick-finance-websocket-api

Contact Email: support@alltick.co

1. Why did we build this?

When building financial applications (such as asset dashboards, quantitative trading bots, backtesting engines), developers often face the following pain points:

• Expensive data: Professional financial terminals (such as Bloomberg, Refinitiv) cost thousands of dollars per month, which is unaffordable for most individual developers.

• Fragmented APIs: You need a separate API for stocks, another for crypto, and yet another for forex, leading to extremely high maintenance costs.

• High latency: Many free interfaces only update at minute-level granularity, which cannot support tick-level real-time market analysis.

• Difficult integration: Inconsistent data formats, poor WebSocket stability, and complex reconnection logic create significant integration challenges.

AllTick API's goal is to solve the "last 100 meters" problem of accessing global multi-market data through a unified, high-performance interface.

2. Core Features

2.1 Full asset coverage:

• Stocks: Full coverage of A-shares (complete market), US stocks (complete market), and Hong Kong stocks (complete market).

• Forex: 60+ currency pairs with tick-level updates.

• Cryptocurrencies: Real-time quotes and depth data for mainstream varieties.

• Commodities: Gold, crude oil, natural gas, and more.

2.2 Real-time tick-level push: Full-duplex data push based on WebSocket, with an average latency of only around 170ms, suitable for high-frequency monitoring.

2.3 Historical data backtesting: Provides historical K-line data from minute-level to monthly-level, supporting quantitative strategy backtesting.

2.4 Simple integration: Data is returned in a unified JSON format, with SDKs available for multiple languages including Python, PHP, Java, and Go.

2.5 High availability: 99.95% service availability (SLA), with support for automatic heartbeat detection and reconnection mechanisms.

3. Who is this for?

• Fintech companies: Use it as a low-cost, highly stable underlying market data source
• Quantitative traders: Build strategy backtesting engines, high-frequency arbitrage bots, and real-time risk control systems
• Independent developers: Build personal asset management tools, financial quote websites, Telegram price alert bots, and more.