Tai
A composable, real-time market data and trade execution toolkit for orchestrating trading across multiple venues.
What is Tai?
Tai is a composable, real-time market data and trade execution toolkit built with Elixir and running on the Erlang virtual machine. It enables developers to stream market data and manage orders with a near-uniform API across multiple cryptocurrency and derivatives exchanges, providing a powerful foundation for building automated trading systems.
Developers building automated trading systems, algorithmic trading bots, or real-time financial data pipelines, particularly those working with Elixir/Erlang ecosystems and needing multi-exchange integration.
Developers choose Tai for its composable architecture that allows customization for specific trading strategies, its near-uniform API that simplifies integration across multiple venues, and its real-time capabilities powered by the concurrent, robust foundation of the Erlang VM.
Overview
A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
Use Cases
Best For
- Building automated trading systems that require real-time market data streaming from multiple cryptocurrency exchanges.
- Developing algorithmic trading strategies that need a unified API to manage orders across different venues like FTX, OkEx, and BitMEX.
- Creating composable trading toolkits where developers can extend and customize components to fit specific workflows.
- Implementing real-time financial data pipelines that leverage Elixir's concurrency and the Erlang VM's robustness.
- Managing live order books, accounts, orders, products, and fees across supported exchanges through a single toolkit.
- Orchestrating trading operations that require integration with both spot and derivatives markets via a consistent interface.
Not Ideal For
- Teams needing immediate, full-featured support for a wide range of exchanges beyond FTX, OkEx, and BitMEX
- Developers unfamiliar with Elixir who prefer more mainstream languages like Python for trading systems
- Simple trading bots that only interact with a single exchange and don't require a unified multi-venue API
- Projects focused on traditional financial markets (e.g., stocks, forex) rather than cryptocurrency and derivatives
Pros & Cons
Pros
Streams live market data from fully supported exchanges like FTX, OkEx, and BitMEX, providing a unified API for order books, accounts, and orders as shown in the supported venues table.
Designed as a toolkit that allows developers to extend and customize components to fit specific trading strategies, aligning with the philosophy of composability and real-time responsiveness.
Leverages the Erlang virtual machine for high concurrency and fault tolerance, ideal for building robust, real-time trading systems as highlighted in the project description.
Offers tools to create, manage, and track orders across multiple venues with a near-uniform API, simplifying development and reducing integration complexity.
Cons
Many listed venues are in progress or lack key features; for example, Binance and Deribit do not support orders yet, limiting immediate usability for those exchanges.
Requires proficiency in Elixir and Erlang, which may be a barrier for teams accustomed to more common trading languages, as indicated by the installation requirements.
Installation involves mix tasks, database setup (SQLite or PostgreSQL), and migrations, with upgrades requiring regenerating and running migrations, adding complexity compared to simpler libraries.
Frequently Asked Questions
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