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flanglet/kanzi-cpp: Fast lossless data compression in C++

Kanzi is a modern, modular, portable, and efficient lossless data compressor written in C++.

Unlike most mainstream lossless compressors, Kanzi is not limited to a single compression paradigm. By combining multiple algorithms and techniques, it supports a broader range of compression ratios and adapts better to diverse data types.

Most traditional compressors underutilize modern hardware by running single-threaded—even on machines with many cores. Kanzi, in contrast, is concurrent by design, compressing multiple blocks in parallel across threads for significant performance gains. However, it is not compatible with standard compression formats.

It’s important to note that Kanzi is a data compressor, not an archiver. It includes optional checksums for verifying data integrity, but does not provide features like cross-file deduplication or data recovery mechanisms. That said, it produces a seekable bitstream—meaning one or more consecutive blocks can be decompressed independently, without needing to process the entire stream.

For more details, see Wiki, Q&A and DeepWiki

See how to reuse the C and C++ APIs: here

There is a Java implementation available here: https://github.com/flanglet/kanzi

There is a Go implementation available here: https://github.com/flanglet/kanzi-go

There are already many excellent, open-source lossless data compressors available.

If gzip is beginning to show its age, modern alternatives like zstd and brotli offer compelling replacements. Both are open-source, standardized, and used daily by millions. Zstd is especially notable for its exceptional speed and is often the best choice in general-purpose compression.

However, there are scenarios where Kanzi may offer superior performance:

While gzip, LZMA, brotli, and zstd are all based on LZ (Lempel-Ziv) compression, they are inherently limited in the compression ratios they can achieve. Kanzi goes further by incorporating BWT (Burrows-Wheeler Transform) and CM (Context Modeling), which can outperform traditional LZ-based methods in certain cases.

LZ-based compressors are ideal for software distribution, where data is compressed once and decompressed many times, thanks to their fast decompression speeds—though they tend to be slower when compressing at higher ratios. But in other scenarios—such as real-time data generation, one-off data transfers, or backups—compression speed becomes critical. Here, Kanzi can shine.

Kanzi also features a suite of built-in, customizable data transforms tailored for specific data types (e.g., multimedia, UTF, text, DNA, etc.), which can be selectively applied during compression for better efficiency.

Furthermore, Kanzi is designed to leverage modern multi-core CPUs to boost performance.

Finally, extensibility is a key strength: implementing new transforms or entropy codecs—whether for experimentation or to improve performance on niche data types—is straightforward and developer-friendly.

Test machine:

Apple M3 24 GB Sonoma 14.6.1

Kanzi version 2.4.0 C++ implementation

On this machine, Kanzi uses 4 threads (half of CPUs by default).

bzip3 runs with 4threads.

zstd and lz4 use 4 threads for compression and 1 for decompression, other compressors are single threaded.

The default block size at level 9 is 32MB, severely limiting the number of threads in use, especially with enwik8, but all tests are performed with default values.

Download at http://sun.aei.polsl.pl/~sdeor/corpus/silesia.zip

Compressor Encoding (ms) Decoding (ms) Size Original 211,957,760 kanzi -l 1 461 252 80,245,856 lz4 1.1.10 -T4 -4 527 121 79,919,901 zstd 1.5.8 -T4 -2 147 150 69,410,383 kanzi -l 2 326 270 68,860,099 brotli 1.1.0 -2 907 402 68,039,159 Apple gzip 430.140.2 -9 10406 273 67,648,481 kanzi -l 3 684 344 64,266,936 zstd 1.5.8 -T4 -5 300 154 62,851,716 kanzi -l 4 802 463 61,131,554 zstd 1.5.8 -T4 -9 752 137 59,190,090 brotli 1.1.0 -6 3596 340 58,557,128 zstd 1.5.8 -T4 -13 4537 138 57,814,719 brotli 1.1.0 -9 19809 329 56,414,012 bzip2 1.0.8 -9 9673 3140 54,602,583 kanzi -l 5 2087 1248 54,025,588 zstd 1.5.8 -T4 -19 20482 151 52,858,610 kanzi -l 6 3065 2329 49,521,392 xz 5.8.1 -9 48516 1594 48,774,000 kanzi -l 7 3798 3298 47,312,772 bzip3 1.5.1.r3-g428f422 -j 4 8559 3948 47,256,794 kanzi -l 8 14712 16009 43,260,254 kanzi -l 9 20395 22375 41,858,030

Download at https://mattmahoney.net/dc/enwik8.zip

Apple M3 24 GB Sonoma 14.6.1

Compressor Encoding (ms) Decoding (ms) Size Original 100,000,000 kanzi -l 1 271 135 43,644,013 kanzi -l 2 196 142 37,570,404 kanzi -l 3 350 200 32,466,232 kanzi -l 4 372 249 29,536,517 kanzi -l 5 720 478 26,523,940 kanzi -l 6 1053 807 24,076,765 kanzi -l 7 1704 1416 22,817,360 kanzi -l 8 6544 6988 21,181,992 kanzi -l 9 8194 9090 20,035,144

Comprehensive lzbench benchmarks

More round trip scores

The C++ code can be built on Windows with Visual Studio, Linux, macOS and Android with g++ and/or clang++. There are no dependencies. Porting to other operating systems should be straightforward.

Unzip the file "Kanzi_VS2008.zip" in place. The solution generates a Windows 32 binary. Multithreading is not supported with this version.

Unzip the file "Kanzi_VS2022.zip" in place. The solution generates a Windows 64 binary and library. Multithreading is supported with this version.

Go to the source directory and run 'make clean && mingw32-make.exe kanzi'. The Makefile contains all the necessary targets. Tested successfully on Win64 with mingw-w64 g++ 8.1.0. Multithreading is supportedwith g++ version 5.0.0 or newer. Builds successfully with C++11, C++14, C++17.

Go to the source directory and run 'make clean && make kanzi'. The Makefile contains all the necessary targets. Build successfully on Ubuntu with many versions of g++ and clang++. Multithreading is supported with g++ version 5.0.0 or newer. Builds successfully with C++98, C++11, C++14, C++17, C++20.

Go to the source directory and run 'make clean && make kanzi'. The Makefile contains all the necessary targets. Build successfully on MacOs with several versions of clang++. Multithreading is supported.

The makefile uses the gnu-make syntax. First, make sure gmake is present (or install it: 'pkg install gmake'). Go to the source directory and run 'gmake clean && gmake kanzi'. The Makefile contains all the necessary targets. Multithreading is supported.

clean:     removes objects, libraries and binaries
kanzi:     builds the kanzi executable
lib:       builds static and dynamic libraries
test:      builds test binaries
all:       kanzi + lib + test
install:   installs libraries, headers and executable
uninstall: removes installed libraries, headers and executable

For those who prefer cmake, run the following commands:

mkdir build
cd build
cmake ..
make

Credits

Matt Mahoney, Yann Collet, Jan Ondrus, Yuta Mori, Ilya Muravyov, Neal Burns, Fabian Giesen, Jarek Duda, Ilya Grebnov

Disclaimer

Use at your own risk. Always keep a copy of your original files.


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