Rusdis: A Redis-like Key-Value Store in Rust

Rusdis is a lightweight, high-performance, in-memory key-value store built from scratch in Rust. It mimics the basic functionalities of Redis, with a focus on simplicity, performance, and leveraging Rust's safety guarantees.

Features

• In-Memory Storage: Fast data retrieval using an in-memory architecture.
• Key-Value Operations:
  • SET and GET commands for storing and retrieving values.
  • DEL for deleting keys.
• Data Persistence:
  • Append-only file (AOF) support for durable storage.
  • Periodic snapshots using a custom implementation of RDB-like persistence.
• Concurrency: Multi-threaded request handling using Rust's async capabilities.
• Customizable: Configurable memory limits, persistence intervals, and more.
• Extensible: Modular design allows easy extension of features.

Getting Started

Prerequisites

• Rust (minimum version: 1.77.0)

Installation

1. Clone the repository:

   git clone https://github.com/your-username/rusdis.git
   cd rusdis

2. Build the project:

   cargo build --release

3. Run the server:

   cargo run --release

4. Use any Redis-compatible client (e.g., redis-cli):

   redis-cli -h 127.0.0.1 -p 6379

Usage

Example Commands:

SET key value
GET key
DEL key

Configuration:

• port: Port number for the server (default: 6379)
• dir: Directory to store RDB file
• dbfilename: Name of the RDB file
• replicaof: Master's port number to listen to

cargo run --release -- --dir /path/to/rdbfile --dbfilename backup.rdb --port 6380 --replicaof 6379

Architecture

• Storage Engine: Implements a hash map for fast key-value access, with optional expiration times.
• Persistence:
  • AOF: Logs all write operations for recovery after restarts.
  • Snapshots: Periodic full-disk dumps of the in-memory state.
• Networking: Uses tokio for asynchronous request handling.
• Command Parser: Parses Redis-like commands from clients.

Roadmap

• Add support for pub/sub functionality.
• Implement clustering for horizontal scaling.
• Introduce more advanced data structures like lists, sets, and sorted sets.
• Enhance security with authentication mechanisms.
• Improve AOF compression and performance.