kanzi-go

Kanzi

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

• Modern: Kanzi implements state-of-the-art compression algorithms and is built to fully utilize multi-core CPUs via built-in multi-threading.
• Modular: Entropy codecs and data transforms can be selected and combined at runtime to best suit the specific data being compressed.
• Expandable: A clean, interface-driven design—with no external dependencies—makes Kanzi easy to integrate, extend, and customize.
• Efficient: Carefully optimized to balance compression ratio and speed for practical, high-performance usage.

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 code here: https://github.com/flanglet/kanzi-go/wiki/Using-and-extending-the-code

There is a C++ implementation available here: https://github.com/flanglet/kanzi-cpp

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

Why Kanzi

While excellent open-source compressors like zstd and brotli exist, they are primarily based on Lempel-Ziv (LZ) algorithms. Zstd, in particular, is a fantastic general-purpose choice known for its speed. However, LZ-based tools have inherent limits regarding compression ratios.

Kanzi offers a compelling alternative for specific high-performance scenarios:

• Beyond LZ: By incorporating Burrows-Wheeler Transform (BWT) and Context Modeling (CM), Kanzi can achieve compression ratios that traditional LZ methods cannot.

• Speed where it counts: While LZ is ideal for "compress once, decompress often" (like software distribution), it often slows down significantly at high compression settings. Kanzi leverages multi-core CPUs to maintain performance, making it highly effective for backups, real-time data generation, and one-off transfers.

• Content-Aware: Kanzi features built-in, customizable transforms for specific data types (e.g., multimedia, DNA, UTF text), improving efficiency where generic compressors fail.

• Extensible: The architecture is developer-friendly, making it straightforward to implement new transforms or entropy codecs for experimentation or niche data types.

Benchmarks

Kanzi version 2.6.0

silesia.tar

Test machine: AMD Ryzen 9950X on Ubuntu 26.04

Go version 1.27.1

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

Compressor	Encoding (ms)	Decoding (ms)	Size
Original			211,957,760
lz4 1.1.10 -T16 -4	18	13	79,910,851
kanzi -l 1	157	69	79,184,957
zstd 1.6.0 -T16 -2	57	25	69,443,247
kanzi -l 2	137	84	68,627,321
brotli 1.1.0 -2	880	333	68,040,160
gzip 1.13 -9	10328	704	67,651,076
kanzi -l 3	232	111	63,093,409
zstd 1.6.0 -T16 -5	136	26	62,867,556
kanzi -l 4	439	191	60,789,646
zstd 1.6.0 -T16 -9	322	24	59,233,481
brotli 1.1.0 -6	4039	299	58,511,709
zstd 1.6.0 -T16 -13	1820	26	57,843,283
brotli 1.1.0 -9	23030	293	56,407,229
bzip2 1.0.8 -9	8223	3453	54,588,597
kanzi -l 5	900	462	53,863,205
zstd 1.6.0 -T16 -19	11090	23	52,830,213
kanzi -l 6	1295	1056	49,472,110
xz 5.8.1 -9	43611	931	48,802,580
bsc 3.3.11 -T16	1201	698	47,900,848
kanzi -l 7	1628	1184	47,330,431
bzip3 1.5.1.r3-g428f422 -j 16	2348	2218	42,962,926
kanzi -l 8	7597	7791	42,962,913
kanzi -l 9	16397	16991	41,520,677

enwik8

Test machine: Apple M3 24 GB Sonoma 15.7.3

Go version 1.26.1

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

Compressor	Encoding (ms)	Decoding (ms)	Size
Original			100,000,000
Kanzi -l 1	169	51	42,941,668
Kanzi -l 2	161	67	37,688,371
Kanzi -l 3	262	124	32,562,496
Kanzi -l 4	415	183	29,466,291
Kanzi -l 5	776	419	26,521,279
Kanzi -l 6	1269	985	24,076,777
Kanzi -l 7	2090	1670	22,817,366
Kanzi -l 8	7960	7835	21,181,998
Kanzi -l 9	10104	10888	20,035,687

Build

Using formal releases is recommended (see https://github.com/flanglet/kanzi-go/releases).

go install github.com/flanglet/kanzi-go/v2/[email protected]

Otherwise, to build manually from the latest tag, follow the instructions below:

git clone https://github.com/flanglet/kanzi-go.git

cd kanzi-go/v2/app

go build Kanzi.go BlockCompressor.go BlockDecompressor.go InfoPrinter.go

The bistream is backward compatible, however, the guarantee only applies to releases. Users can expect incompatibilities or breakage due to bitstream changes in between releases.

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.