OKX Exchange Connector in C++: High-Performance Crypto Data Retrieval with REST and WebSocket

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Introduction

In today's fast-moving cryptocurrency markets, real-time data access is essential for algorithmic trading, market analysis, and high-frequency strategies. The OKX Exchange Connector in C++ is a powerful open-source tool designed to deliver low-latency access to critical trading data from the OKX exchange. Built entirely in C++, this lightweight yet robust application enables developers to retrieve Level 1 Limit Order Book (LOB) data for BTC-USDT with exceptional speed—under 100ms when using WebSocket and less than one second via REST API.

Whether you're building a custom trading bot, conducting quantitative research, or developing performance-critical financial applications, this connector provides a solid foundation for real-time market data ingestion.

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Key Features of the OKX C++ Connector

This project stands out due to its focus on performance, simplicity, and parallel processing capability. Below are the core functionalities it delivers:

1. Native OKX API Integration

The application connects directly to the OKX Crypto Exchange API using standard HTTP requests without relying on third-party libraries for REST communication. This ensures minimal overhead and maximum control over network behavior.

For ultra-low-latency use cases, the WebSocket implementation leverages the WebSocket++ library to maintain a persistent connection, enabling near-instantaneous updates as market conditions change.

2. Real-Time Level 1 LOB Data Extraction

One of the primary objectives of this tool is to continuously fetch the latest Level 1 Limit Order Book (LOB) data for the BTC-USDT trading pair. This includes:

With sub-second latency over REST and sub-100ms response times via WebSocket, the connector supports time-sensitive operations crucial for algorithmic trading systems.

3. Parallel Execution Architecture

A standout feature of this implementation is its ability to run two intensive tasks simultaneously:

This demonstrates effective use of threading or asynchronous execution models in C++, ensuring that data fetching does not block expensive computations—and vice versa.

4. Built-In Stress Testing via Calculation Class

To simulate real-world workloads, the project includes a dedicated CalculationClass that performs memory- and CPU-intensive operations. Specifically, it solves the matrix equation AX = E, where:

This task mimics complex quantitative calculations used in risk modeling, portfolio optimization, and derivative pricing.

By running this alongside live market data collection, developers can evaluate system stability under load—a critical factor when deploying trading infrastructure.

Technical Requirements

To build and run this application, you'll need the following:

Alternatively, the project supports automated builds using CMake and Conan, streamlining dependency management and cross-platform compilation.

How to Build and Run

You can compile and execute the application using either direct compilation commands or through CMake and Conan for better scalability.

Option 1: Direct Compilation

For REST Version:

g++ main.cpp -o main CalculationClass.cpp OKXClass.cpp -lcurl -lssl -lcrypto

For WebSocket Version:

g++ main.cpp -o main CalculationClass.cpp WebSocketClass.cpp -lssl -lcrypto

After compilation, run the executable:

./main

Option 2: Using CMake and Conan (Recommended)

  1. Install Conan (C/C++ package manager).

  2. Run Conan to install dependencies:

    conan install . --output-folder=build --build=missing

  3. Navigate to the build directory and configure with CMake:

    cd build
cmake .. -DCMAKE_TOOLCHAIN_FILE=./build/Release/generators/conan_toolchain.cmake -DCMAKE_BUILD_TYPE=Release
cmake --build .

  4. Execute the built binary:

    ./WebSocket/websocket_client

This method ensures consistent builds across different environments and simplifies integration into larger development pipelines.

Project File Structure

The repository is cleanly organized into two main modules: REST and WebSocket, each containing independent implementations of the core logic.

- REST/
  - main.cpp
  - CalculationClass.h/cpp
  - OKXClass.h/cpp
- WebSocket/
  - main.cpp
  - CalculationClass.h/cpp
  - WebSocketClass.h/cpp

Core Components Explained

main.cpp

Contains the entry point and orchestrates parallel execution between market data collection and computational tasks. It logs key metrics such as:

CalculationClass.h/cpp

Implements the CalculationClass, responsible for solving AX = E by computing the inverse of a matrix using numerical methods like Gaussian elimination or LU decomposition. This serves as a benchmark for CPU/memory load.

OKXClass.h/cpp (REST)

Manages HTTP-based communication with OKX using libcurl. Handles:

WebSocketClass.h/cpp (WebSocket)

Establishes a persistent WebSocket connection to OKX’s real-time feed. Key responsibilities include:

Why Use C++ for Crypto Market Connectivity?

C++ remains a top choice for performance-critical financial applications due to:

These traits make it ideal for building low-latency connectors that must process thousands of messages per second—exactly what’s needed when interfacing with exchanges like OKX.

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Core Keywords

To enhance discoverability and align with user search intent, here are the primary keywords naturally integrated throughout this article:

These terms reflect common queries among developers building automated trading systems or studying quantitative finance.

Frequently Asked Questions (FAQ)

Q: Can I use this connector for other trading pairs besides BTC-USDT?
A: Yes. While BTC-USDT is used as the default example, the code can be easily modified to support other symbols supported by the OKX API by updating the request parameters.

Q: Is authentication included for private API endpoints?
A: No. This implementation focuses on public market data only (e.g., ticker, order book). Adding private account functionality would require signing requests with API keys, which is outside the current scope.

Q: How accurate is the latency measurement?
A: Latency is measured from request initiation to response receipt. In tests, WebSocket achieves under 100ms round-trip time in optimal network conditions.

Q: Can I integrate this into a larger trading system?
A: Absolutely. The modular design makes it easy to embed the OKXClass or WebSocketClass into broader algorithmic trading frameworks.

Q: What happens if the WebSocket connection drops?
A: The current version does not include auto-reconnect logic, but implementing reconnection handlers is straightforward using WebSocket++’s event model.

Q: Is there support for Level 2 or Level 3 order book data?
A: Not currently. The project retrieves Level 1 data only. Extending it to deeper book levels requires subscribing to full order book channels via WebSocket.

Final Thoughts

The OKX Exchange Connector in C++ offers a lean, efficient way to access real-time cryptocurrency market data with minimal dependencies and high performance. Its dual-mode architecture—supporting both REST and WebSocket protocols—makes it adaptable for various use cases, from educational projects to production-grade trading engines.

Developers looking to explore low-latency systems will find this repository an excellent starting point for understanding real-time data pipelines in C++.

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