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Zstandard - Fast real-time compression algorithm

Zstandard is a fast lossless compression algorithm, targeting real-time compression scenarios. It provides a very wide range of compression ratios, while typically offering faster compression and decompression speeds compared to other algorithms.

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Added on 2025年5月12日
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Project Introduction

Summary

Zstandard, or zstd, is a fast lossless compression algorithm developed by Facebook. It's designed to be efficient for real-time data compression and decompression, making it ideal for scenarios where both speed and compression ratio are important.

Problem Solved

In many computing scenarios, there is a trade-off between data compression ratio and processing speed. Traditional algorithms often prioritize one over the other. Zstandard addresses this by offering a balanced solution that delivers high compression ratio while maintaining very fast compression and decompression speeds, crucial for real-time data handling.

Core Features

High Performance

Offers excellent compression and decompression speeds, suitable for real-time applications and high-throughput systems.

Strong Compression Ratio

Provides a high compression ratio, effectively reducing data size across various data types.

Tunable Compression Levels

Allows selection from a broad range of compression levels, enabling fine-tuning between speed and compression ratio.

Tech Stack

C
C++

使用场景

Zstandard's combination of speed and efficiency makes it suitable for a variety of use cases:

数据库和存储系统

Details

Used for compressing data within databases and storage systems (like RocksDB, Ceph, Hadoop) to save disk space and I/O bandwidth.

User Value

Reduces storage footprint and improves read/write performance.

网络数据传输

Details

Applied to compress data streams in network protocols to reduce transmission latency and bandwidth consumption.

User Value

Speeds up data transfer and lowers networking costs.

日志归档与备份

Details

Compressing log files and backups for efficient storage and faster retrieval.

User Value

Optimizes archive storage and accelerates data recovery.

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