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Zstandard, orzstd as short version, is a fast lossless compression algorithm,targeting real-time compression scenarios at zlib-level and better compression ratios.It's backed by a very fast entropy stage, provided byHuff0 and FSE library.

Zstandard's format is stable and documented inRFC8878. Multiple independent implementations are already available.This repository represents the reference implementation, provided as an open-source dualBSD ORGPLv2 licensedC library,and a command line utility producing and decoding.zst,.gz,.xz and.lz4 files.Should your project require another programming language,a list of known ports and bindings is provided onZstandard homepage.

Development branch status:

For reference, several fast compression algorithms were tested and comparedon a desktop featuring a Core i7-9700K CPU @ 4.9GHzand running Ubuntu 24.04 (Linux 6.8.0-53-generic),usinglzbench, an open-source in-memory benchmark by @inikepcompiled withgcc 14.2.0,on theSilesia compression corpus.

The negative compression levels, specified with--fast=#,offer faster compression and decompression speedat the cost of compression ratio.

Zstd can also offer stronger compression ratios at the cost of compression speed.Speed vs Compression trade-off is configurable by small increments.Decompression speed is preserved and remains roughly the same at all settings,a property shared by most LZ compression algorithms, such aszlib or lzma.

The following tests were runon a server running Linux Debian (Linux version 4.14.0-3-amd64)with a Core i7-6700K CPU @ 4.0GHz,usinglzbench, an open-source in-memory benchmark by @inikepcompiled withgcc 7.3.0,on theSilesia compression corpus.

Compression Speed vs Ratio	Decompression Speed

A few other algorithms can produce higher compression ratios at slower speeds, falling outside of the graph.For a larger picture including slow modes,click on this link.

Previous charts provide results applicable to typical file and stream scenarios (several MB). Small data comes with different perspectives.

The smaller the amount of data to compress, the more difficult it is to compress. This problem is common to all compression algorithms, and reason is, compression algorithms learn from past data how to compress future data. But at the beginning of a new data set, there is no "past" to build upon.

To solve this situation, Zstd offers atraining mode, which can be used to tune the algorithm for a selected type of data.Training Zstandard is achieved by providing it with a few samples (one file per sample). The result of this training is stored in a file called "dictionary", which must be loaded before compression and decompression.Using this dictionary, the compression ratio achievable on small data improves dramatically.

The following example uses thegithub-userssample set, created fromgithub public API.It consists of roughly 10K records weighing about 1KB each.

Compression Ratio	Compression Speed	Decompression Speed

These compression gains are achieved while simultaneously providingfaster compression and decompression speeds.

Training works if there is some correlation in a family of small data samples. The more data-specific a dictionary is, the more efficient it is (there is nouniversal dictionary).Hence, deploying one dictionary per type of data will provide the greatest benefits.Dictionary gains are mostly effective in the first few KB. Then, the compression algorithm will gradually use previously decoded content to better compress the rest of the file.

1. Create the dictionary

   zstd --train FullPathToTrainingSet/* -o dictionaryName

2. Compress with dictionary

   zstd -D dictionaryName FILE

3. Decompress with dictionary

   zstd -D dictionaryName --decompress FILE.zst

make is the officially maintained build system of this project.All other build systems are "compatible" and 3rd-party maintained,they may feature small differences in advanced options.When your system allows it, prefer usingmake to buildzstd andlibzstd.

If your system is compatible with standardmake (orgmake),invokingmake in root directory will generatezstd cli in root directory.It will also createlibzstd intolib/.

Other available options include:

• make install : create and install zstd cli, library and man pages
• make check : create and runzstd, test its behavior on local platform

TheMakefile follows theGNU Standard Makefile conventions,allowing staged install, standard flags, directory variables and command variables.

For advanced use cases, specialized compilation flags which control binary generationare documented inlib/README.md for thelibzstd libraryand inprograms/README.md for thezstd CLI.

Acmake project generator is provided withinbuild/cmake.It can generate Makefiles or other build scriptsto createzstd binary, andlibzstd dynamic and static libraries.

By default,CMAKE_BUILD_TYPE is set toRelease.

zstd can be built and installed with support for both Apple Silicon (M1/M2) as well as Intel by using CMake's Universal2 support.To perform a Fat/Universal2 build and install use the following commands:

cmake -B build-cmake-debug -S build/cmake -G Ninja -DCMAKE_OSX_ARCHITECTURES="x86_64;x86_64h;arm64"cd build-cmake-debugninjasudo ninja install

A Meson project is provided withinbuild/meson. Followbuild instructions in that directory.

You can also take a look at.travis.yml file for anexample about how Meson is used to build this project.

Note that default build type isrelease.

You can build and install zstdvcpkg dependency manager:

git clone https://github.com/Microsoft/vcpkg.gitcd vcpkg./bootstrap-vcpkg.sh./vcpkg integrate install./vcpkg install zstd

The zstd port in vcpkg is kept up to date by Microsoft team members and community contributors.If the version is out of date, pleasecreate an issue or pull request on the vcpkg repository.

You can install pre-built binaries for zstd or build it from source usingConan. Use the following command:

conan install --requires="zstd/[*]" --build=missing

The zstd Conan recipe is kept up to date by Conan maintainers and community contributors.If the version is out of date, pleasecreate an issue or pull request on the ConanCenterIndex repository.

Going intobuild directory, you will find additional possibilities:

• Projects for Visual Studio 2005, 2008 and 2010.
  • VS2010 project is compatible with VS2012, VS2013, VS2015 and VS2017.
• Automated build scripts for Visual compiler by@KrzysFR, inbuild/VS_scripts,which will buildzstd cli andlibzstd library without any need to open Visual Studio solution.

You can build the zstd binary via buck by executing:buck build programs:zstd from the root of the repo.The output binary will be inbuck-out/gen/programs/.

You easily can integrate zstd into your Bazel project by using the module hosted on theBazel Central Repository.

You can run quick local smoke tests by runningmake check.If you can't usemake, execute theplayTest.sh script from thesrc/tests directory.Two env variables$ZSTD_BIN and$DATAGEN_BIN are needed for the test script to locate thezstd anddatagen binary.For information on CI testing, please refer toTESTING.md.

Zstandard is currently deployed within Facebook and many other large cloud infrastructures.It is run continuously to compress large amounts of data in multiple formats and use cases.Zstandard is considered safe for production environments.

Zstandard is dual-licensed underBSD ORGPLv2.

Thedev branch is the one where all contributions are merged before reachingrelease.If you plan to propose a patch, please commit into thedev branch, or its own feature branch.Direct commit torelease are not permitted.For more information, please readCONTRIBUTING.