google/brotli

Brotli compression format

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Summary Information

Updated 46 minutes ago
Added to GitGenius on September 4th, 2026
Created on October 9th, 2014
Open Issues & Pull Requests: 109 (+0)
GitHub issues: Enabled
Number of forks: 1,358
Total Stargazers: 14,866 (+0)
Total Subscribers: 323 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.7 days
Mean response time: 47.4 days
90th percentile: 131.9 days
Tracked items: 64

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 94% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 4% of issues opened in the past year have been closed. Three people close 67% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 32
New in 7 days: 2
Closed in 7 days: 1
Avg open age: 493 days
Stale 30+ days: 29
Stale 90+ days: 25

Recent activity

Opened in 7 days: 2
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 1

Top labels

  • release-v1.1.1 (2)

Detailed Description

Brotli is a lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding, and second-order context modeling, achieving compression ratios comparable to the best general-purpose compression methods while maintaining speed similar to deflate.

The tool solves the problem of achieving dense compression for data transmission and storage. It combines three techniques: a modern LZ77 variant for pattern matching, Huffman coding for entropy encoding, and second-order context modeling to improve compression ratios. The algorithm is defined in RFC 7932 and works as a stream format without embedded metadata like checksums or uncompressed data length.

Brotli suits projects requiring efficient compression where file size matters more than absolute speed. It is widely available through standard package managers on Linux and macOS, and can be installed via vcpkg, built with CMake or Bazel, or installed as a Python module through pip. The tool is appropriate for web content delivery, data archival, and any scenario where compression density outweighs decompression latency concerns. Users should be aware that as a stream format, it does not include checksums or uncompressed length information, meaning raw ranges of the compressed stream could theoretically be modified without detection.

The project maintains continuous integration through automated build and test workflows. The codebase undergoes fuzzing to identify potential vulnerabilities and edge cases in the compression and decompression logic.