The Ultimate Guide to Brotli Compression

Brotli offers 11 quality levels for compression, ranging from 1 to 11. Higher quality levels result in better compression ratios but can slow down the compression speed. Modern web browsers widely support Brotli, with about 94% of users having access to Brotli-supported browsers.

Studies show that Brotli outperforms GZIP in several key areas. For instance, Brotli achieves up to 14% better compression for JavaScript files, 17% for CSS files, and 21% for HTML files. These percentages highlight the efficiency of Brotli compression.

Brotli supports various formats, including text and application types such as text/xml, text/plain, text/css, and application/javascript. This versatility makes it adaptable for a range of use-cases.

Designed for on-the-fly compression, Brotli is faster than GZIP both in compressing content on the server and decompressing it on the client side. In some scenarios, the front-end decompression speed can be up to 64% faster than GZIP.

The strongest Brotli compression level, which is 11, reduces file sizes by 19% compared to the best GZIP level. Notably, this level is also about 18% smaller than the default level used by major content delivery networks.

Brotli is a lossless compression algorithm that uses a combination of modern LZ77, Huffman coding, and 2nd order context modeling. It provides a compression ratio comparable to the best general-purpose compression methods currently available.

The best compression standard varies depending on user needs, but ZPAQ and ARC are generally considered the most efficient. However, 7Z and RAR formats tend to decompress faster, which can be an important factor depending on the application.

While Brotli is highly effective, Gzip is another widely used lossless compression algorithm, especially in Unix-based systems. Gzip offers excellent compression ratios while preserving data integrity, making it a popular choice for internet transmission and archival purposes.

For highly compressible data, tests indicate that an optimal compression ratio lies between 85% and 95%. This range provides a good balance between file size reduction and computational efficiency.