gdelta 0.1.0

Fast delta compression algorithm for similar data chunks
Documentation

gdelta

Crates.io Documentation License: MIT

A fast delta compression algorithm for similar data chunks, implemented in pure Rust.

Overview

gdelta is a Rust implementation of the GDelta algorithm by Haoliang Tan. It provides efficient delta encoding for similar data chunks (typically 4KB - 64KB) commonly found in deduplication systems.

Key Features:

  • 🚀 Fast delta encoding and decoding (1 GB/s encode, 5-8 GB/s decode)
  • 🔒 Memory-safe implementation in pure Rust
  • 📦 Simple, ergonomic API
  • ✨ No unsafe code
  • 🧪 Thoroughly tested

Performance:

  • Encoding: 850-1000 MiB/s (~1 GB/s)
  • Decoding: 5-8 GB/s (5-8x faster than encoding)
  • Faster than Xdelta, Zdelta, Ddelta, and Edelta
  • Optimized for inter-chunk redundancy removal
  • Best used with general compression (e.g., ZSTD) for additional compression

Benchmarked on typical hardware with similar data chunks

Installation

Add this to your Cargo.toml:

[dependencies]
gdelta = "0.1"

Usage

use gdelta::{encode, decode};

// Create base data and modified version
let base_data = b"Hello, World! This is some base data.";
let new_data = b"Hello, Rust! This is some modified data.";

// Encode the delta
let delta = encode(new_data, base_data)?;
println!("Delta size: {} bytes", delta.len());

// Decode to recover the new data
let recovered = decode(&delta, base_data)?;
assert_eq!(recovered, new_data);

How It Works

GDelta uses:

  1. GEAR Rolling Hash - Fast fingerprinting for chunk boundaries
  2. Variable-Length Integer Encoding - Efficient space utilization
  3. Copy/Literal Instructions - Minimal delta representation
  4. Prefix/Suffix Matching - Optimized for common data patterns

The algorithm identifies matching regions between base and new data, then encodes only the differences as a series of copy and literal instructions.

Algorithm Parameters

The implementation uses optimized default parameters:

  • Chunk size: 300 KB
  • Word size: 8 bytes
  • Base sample rate: 3
  • Features: Skip optimization, reverse matching

These parameters are tuned for typical deduplication workloads.

Comparison with Other Delta Algorithms

Feature GDelta Xdelta Zdelta
Speed âš¡âš¡âš¡ âš¡âš¡ âš¡
Memory Low Medium High
Compression Good* Excellent Good

*Use with ZSTD/LZ4 for best compression ratio

Use Cases

  • Deduplication Systems - Compress similar chunks
  • Backup Software - Incremental backups
  • File Synchronization - Minimize transfer size
  • Version Control - Efficient diff storage

Credits

This is a Rust implementation of the GDelta algorithm by Haoliang Tan.

Original repositories/resources:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.