C++ (Backend)

C++ Backend Development

Overview

High-performance C++ backend implementation for real-time data processing, WebSocket servers, REST APIs, and integration with Redis, MongoDB, and AWS S3. Learn how to build scalable, multi-threaded financial services using modern C++17/20 and Boost libraries.

What You’ll Learn

  • Boost.Beast: WebSocket and HTTP servers for real-time quotes
  • Multi-threading: High-performance concurrent data processing
  • REST API Design: Router → Controller → Service architecture
  • Database Integration: MongoDB and DuckDB clients
  • Cloud Services: AWS S3 operations and S3 Select queries
  • Real-time Streaming: Redis Streams for backend integration
  • Modern C++: CMake, dependency injection, and best practices

Key Technologies

  • Boost Libraries: Beast (HTTP/WebSockets), Asio (async I/O), Program Options
  • MongoDB C++ Driver: CRUD operations and data persistence
  • AWS C++ SDK: S3 storage and S3 Select for Parquet files
  • Redis: Streams for inter-service communication
  • DuckDB: In-process analytical database
  • CMake: Modern build system

Documentation Index

Getting Started

  1. Docker Dev Environment Setup - Docker containerization and development environment

WebSocket & Streaming

  1. Boost Beast WebSocket Client - Multi-threaded client to read stock quotes from WebSocket
  2. Boost Beast WebSocket Server - Multi-threaded server to publish stock quotes
  3. Redis Streams - Integrate C++ and Node.js backends using Redis

REST API Development

  1. Boost Beast REST API Server - Multi-threaded REST API server
  2. REST API with CORS - CORS support for cross-origin requests
  3. Router → Controller → Service - Architecture pattern for REST APIs
  4. REST API Models - Use models for JSON output
  5. Fundamentals Controller - Cache S3 presigned URLs in Redis
  6. PnL Controller - Profit & Loss calculations
  7. Quotes Analytics API - Stock quotes analytics endpoints

Database & Storage

  1. MongoDB Client/Service - C++ MongoDB driver for CRUD operations
  2. AWS S3 Client/Service - AWS SDK for S3 CRUD operations
  3. AWS S3 Select - Query Parquet files with S3 Select
  4. DuckDB Service - In-process analytical queries
  5. File Cache Service - File caching for performance

Build & Architecture

  1. Boost Program Options - Command-line argument parsing
  2. CMake - Switch from Make to CMake
  3. Dependency Injection Refactoring - Modern DI patterns

Architecture Patterns

Layered Architecture

Request → Router → Controller → Service → Database/External API

Multi-threading

  • Async I/O with Boost.Asio
  • Thread pools for concurrent processing
  • Lock-free data structures where applicable

Integration

  • Redis Streams: Message passing between services
  • MongoDB: Document storage
  • S3: Object storage for historical data
  • DuckDB: Fast analytical queries

Quick Start

  1. Start with Docker Dev Environment Setup
  2. Learn Boost Beast WebSockets
  3. Build your first REST API Server
  4. Integrate with MongoDB and S3

Source Code: backend-cpp | Related: Golang | Rust

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