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  2. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    The Generic Compression Benchmark, [14] maintained by Matt Mahoney, tests compression of data generated by random Turing machines. Sami Runsas (the author of NanoZip) maintained Compression Ratings, a benchmark similar to Maximum Compression multiple file test, but with minimum speed requirements.

  3. zstd - Wikipedia

    en.wikipedia.org/wiki/Zstd

    Zstandard was designed to give a compression ratio comparable to that of the DEFLATE algorithm (developed in 1991 and used in the original ZIP and gzip programs), but faster, especially for decompression. It is tunable with compression levels ranging from negative 7 (fastest) [6] to 22 (slowest in compression speed, but best compression ratio).

  4. List of archive formats - Wikipedia

    en.wikipedia.org/wiki/List_of_archive_formats

    The replacement for the .sit format that supports more compression methods, UNIX file permissions, long file names, very large files, more encryption options, data specific compressors (JPEG, Zip, PDF, 24-bit image, MP3). The free StuffIt Expander is available for Windows and OS X. .sqx SQX: Windows: Windows: Yes A royalty-free compressing format

  5. Snappy (compression) - Wikipedia

    en.wikipedia.org/wiki/Snappy_(compression)

    Snappy (previously known as Zippy) is a fast data compression and decompression library written in C++ by Google based on ideas from LZ77 and open-sourced in 2011. [3] [4] It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression.

  6. Deflate - Wikipedia

    en.wikipedia.org/wiki/DEFLATE

    In computing, Deflate (stylized as DEFLATE, and also called Flate [1] [2]) is a lossless data compression file format that uses a combination of LZ77 and Huffman coding.It was designed by Phil Katz, for version 2 of his PKZIP archiving tool.

  7. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:

  8. bzip2 - Wikipedia

    en.wikipedia.org/wiki/Bzip2

    bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm.It only compresses single files and is not a file archiver.It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting.

  9. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy. The Lempel–Ziv (LZ) compression methods are among the most popular algorithms for lossless storage. [6] DEFLATE is a variation on LZ optimized for decompression speed and compression ratio, [7] but compression