c-blosc - A blocking, shuffling and loss-less compression library that can be faster than `memcpy()`

  •        75

Blosc is a high performance compressor optimized for binary data. It has been designed to transmit data to the processor cache faster than the traditional, non-compressed, direct memory fetch approach via a memcpy() OS call. Blosc is the first compressor (that I'm aware of) that is meant not only to reduce the size of large datasets on-disk or in-memory, but also to accelerate memory-bound computations. It uses the blocking technique so as to reduce activity in the memory bus as much as possible. In short, this technique works by dividing datasets in blocks that are small enough to fit in caches of modern processors and perform compression / decompression there. It also leverages, if available, SIMD instructions (SSE2, AVX2) and multi-threading capabilities of CPUs, in order to accelerate the compression / decompression process to a maximum.

http://blosc.org
https://github.com/Blosc/c-blosc

Tags
Implementation
License
Platform

   




Related Projects

bcolz - A columnar data container that can be compressed.

  •    C

bcolz provides columnar, chunked data containers that can be compressed either in-memory and on-disk. Column storage allows for efficiently querying tables, as well as for cheap column addition and removal. It is based on NumPy, and uses it as the standard data container to communicate with bcolz objects, but it also comes with support for import/export facilities to/from HDF5/PyTables tables and pandas dataframes. bcolz objects are compressed by default not only for reducing memory/disk storage, but also to improve I/O speed. The compression process is carried out internally by Blosc, a high-performance, multithreaded meta-compressor that is optimized for binary data (although it works with text data just fine too).

Lz4 - Extremely Fast Compression algorithm

  •    C

LZ4 is a very fast lossless compression based on well-known LZ77 (Lempel-Ziv) algorithm, providing compression speed at 300 MB/s per core, scalable with multi-cores CPU. It also features an extremely fast decoder, with speeds up and beyond 1GB/s per core, typically reaching RAM speed limits on multi-core systems.

lz4-java - LZ4 compression for Java

  •    C

LZ4 compression for Java, based on Yann Collet's work available at http://code.google.com/p/lz4/. This library provides access to two compression methods that both generate a valid LZ4 stream fast scan (LZ4) and high compression (LZ4 HC). The streams produced by those 2 compression algorithms use the same compression format, are very fast to decompress and can be decompressed by the same decompressor instance.

7-Zip-zstd - 7-Zip with support for Brotli, Fast-LZMA2, Lizard, LZ4, LZ5 and Zstandard

  •    C

Zstandard v1.3.7 is a real-time compression algorithm, providing high compression ratios. It offers a very wide range of compression / speed trade-off, while being backed by a very fast decoder. Brotli v.1.0.7 is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding and 2nd order context modeling, with a compression ratio comparable to the best currently available general-purpose compression methods. It is similar in speed with deflate but offers more dense compression.

lz4 - Extremely Fast Compression algorithm

  •    C

LZ4 is lossless compression algorithm, providing compression speed at 400 MB/s per core, scalable with multi-cores CPU. It features an extremely fast decoder, with speed in multiple GB/s per core, typically reaching RAM speed limits on multi-core systems.Speed can be tuned dynamically, selecting an "acceleration" factor which trades compression ratio for more speed up. On the other end, a high compression derivative, LZ4_HC, is also provided, trading CPU time for improved compression ratio. All versions feature the same decompression speed.


Zstandard - Fast real-time compression algorithm

  •    C

Zstandard is a real-time compression algorithm, providing high compression ratios. It offers a very wide range of compression / speed trade-off, while being backed by a very fast decoder. It also offers a special mode for small data, called dictionary compression, and can create dictionaries from any sample set.

lzham_codec - Lossless data compression codec with LZMA-like ratios but 1

  •    C++

LZHAM is a lossless data compression codec written in C/C++ (specifically C++03), with a compression ratio similar to LZMA but with 1.5x-8x faster decompression speed. It officially supports Linux x86/x64, Windows x86/x64, OSX, and iOS, with Android support on the way. LZHAM is a lossless (LZ based) data compression codec optimized for particularly fast decompression at very high compression ratios with a zlib compatible API. It's been developed over a period of 3 years and alpha versions have already shipped in many products. (The alpha is here: https://code.google.com/p/lzham/) LZHAM's decompressor is slower than zlib's, but generally much faster than LZMA's, with a compression ratio that is typically within a few percent of LZMA's and sometimes better.

SHARC - Fastest lossless compression algorithm

  •    C

SHARC is an extremely fast lossless dictionary-based compression algorithm. It is capable of an unprecedented compression speed of more than 500 MB/s per core on modern Intel CPUs ! It is scalable on multi core/multi CPU, developed in pure C99, and easily portable on many platforms.

lizard - Lizard (formerly LZ5) is an efficient compressor with very fast decompression

  •    C

Lizard library is based on frequently used LZ4 library by Yann Collet but the Lizard compression format is not compatible with LZ4. Lizard library is provided as open-source software using BSD 2-Clause license. The high compression/decompression speed is achieved without any SSE and AVX extensions. The following results are obtained with lzbench and -t16,16 using 1 core of Intel Core i5-4300U, Windows 10 64-bit (MinGW-w64 compilation under gcc 6.2.0) with silesia.tar which contains tarred files from Silesia compression corpus.

FastPFor - The FastPFOR C++ library: Fast integer compression

  •    C++

A research library with integer compression schemes. It is broadly applicable to the compression of arrays of 32-bit integers where most integers are small. The library seeks to exploit SIMD instructions (SSE) whenever possible.This library can decode at least 4 billions of compressed integers per second on most desktop or laptop processors. That is, it can decompress data at a rate of 15 GB/s. This is significantly faster than generic codecs like gzip, LZO, Snappy or LZ4.

compressjs - Pure JavaScript de/compression (bzip2, etc) for node.js, volo, and the browser.

  •    Javascript

compressjs contains fast pure-JavaScript implementations of various de/compression algorithms, including bzip2, Charles Bloom's LZP3, a modified LZJB, PPM-D, and an implementation of Dynamic Markov Compression. compressjs is written by C. Scott Ananian. The Range Coder used is a JavaScript port of Michael Schindler's C range coder. Bits also also borrowed from Yuta Mori's SAIS implementation; Eli Skeggs, Kevin Kwok, Rob Landley, James Taylor, and Matthew Francis for Bzip2 compression and decompression code. "Bear" wrote the original JavaScript LZJB; the version here is based on the node lzjb module. Here are some representative speeds and sizes for the various algorithms implemented in this package. Times are with node 0.8.22 on my laptop, but they should be valid for inter-algorithm comparisons.

lz4 - Extremely Fast Compression algorithm

  •    C

LZ4 is lossless compression algorithm, providing compression speed at 400 MB/s per core, scalable with multi-cores CPU. It also features an extremely fast decoder, with speed in multiple GB/s per core, typically reaching RAM speed limits on multi-core systems.

LZF Compressor- High-performance, streaming/chunking Java LZF codec, compatible with standard C LZF package

  •    Java

LZF-compress is a Java library for encoding and decoding data in LZF format, written by Tatu Saloranta. LZF alfgorithm itself is optimized for speed, with somewhat more modest compression. Compared to the standard Deflate (algorithm gzip uses) LZF can be 5-6 times as fast to compress, and twice as fast to decompress. Compression rate is lower since no Huffman-encoding is used after lempel-ziv substring elimintation.

Snappy Java - Snappy compressor/decompressor for Java

  •    Java

snappy-java is a Java port of the snappy, a fast C++ compresser/decompresser developed by Google. It does fast compression/decompression around 200~400MB/sec, Less memory usage. SnappyOutputStream uses only 32KB+ in default, Compression/decompression of Java primitive arrays (float[], double[], int[], short[], long[], etc.) and lot more.

C# LZF Real-Time Compression Algorithm

  •    

Improved C# LZF Compressor, a very small and extremely efficient real-time data compression library. The compression algorithm is extremely fast. Well suited for real-time data intensive applications (e.g.: packet streaming, embedded devices...).

MessagePack-CSharp - Extremely Fast MessagePack Serializer for C#(

  •    CSharp

Extremely fast MessagePack serializer for C#, x10 faster than MsgPack-Cli and acquires best performance compared with all the other C# serializers. MessagePack for C# has built-in LZ4 compression which can achieve super fast and small binary size. Performance is always important! for Game, Distributed computing, Microservices, Store data to Redis, etc.MessagePack has compact binary size and full set of general purpose expression. Please see the comparison with JSON, protobuf, ZeroFormatter section. If you want to know why MessagePack C# is fastest, please see performance section.

Akumuli - Time-series database

  •    C++

Akumuli is a time-series database for modern hardware. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from Esperanto as "accumulate".

node-lz4 - LZ4 fast compression algorithm for NodeJS

  •    Javascript

LZ4 is a very fast compression and decompression algorithm. This nodejs module provides a Javascript implementation of the decoder as well as native bindings to the LZ4 functions. Nodejs Streams are also supported for compression and decompression. NB. Version 0.2 does not support the legacy format, only the one as of "LZ4 Streaming Format 1.4". Use version 0.1 if required.

FiniteStateEntropy - New generation entropy codecs : Finite State Entropy and Huff0

  •    C

Huff0, a Huffman codec designed for modern CPU, featuring OoO (Out of Order) operations on multiple ALU (Arithmetic Logic Unit), achieving extremely fast compression and decompression speeds.FSE is a new kind of Entropy encoder, based on ANS theory, from Jarek Duda, achieving precise compression accuracy (like Arithmetic coding) at much higher speeds.

Snappy - Port of Snappy to Java

  •    Java

This is a rewrite (port) of Snappy writen in pure Java. This compression code produces a byte-for-byte exact copy of the output created by the original C++ code, and extremely fast.





We have large collection of open source products. Follow the tags from Tag Cloud >>


Open source products are scattered around the web. Please provide information about the open source projects you own / you use. Add Projects.