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.
http://fastcompression.blogspot.in/p/lz4.htmlTags | compression fast decompression data-compression lz77 |
Implementation | C |
License | BSD |
Platform | Windows Linux |
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.
js lz4 lz4-frame compression decompression streamLZ4 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.
lz4-compression jni-bindings compressor lz4-java decompression compression zipZstandard 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.
brotli lizard lz4 lz5 zstd zstandard 7-zip compression archiver 7zLizard 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.
compression compressor fast decompression-speed lz4 brotli zlib efficient zstdLZ4 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.
lz4 compressionBasic Compression Library is a set of open source implementations of RLE (Run Length Encoding), Huffman, Rice, Lempel-Ziv (LZ77) and Shannon-Fano compression algorithms.
compression decompression zib library data-compressionLZHAM 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.
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.
compression decompression data-compression zip libraryBlosc 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.
compression fastSHARC 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.
compression fast decompression data-compression zipA 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.
simd-compression compression-schemes sorted-listsLZ4 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.
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.
compression decompression zip deflate inflatecompressjs 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.
bzip2 compression decompressionLZF-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.
compression decompression zip deflate lzf lzf-compressThis aims to be a complete implementation of XZ data compression in pure Java. Single-threaded streamed compression and decompression and random access decompression have been fully implemented. Threading is planned but it is unknown when it will be implemented.
compression zip archive decompression libraryBrotli 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.The specification of the Brotli Compressed Data Format is defined in RFC 7932.
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.
messagepack unity serialization xamarin c-sharp msgpack lz4Brotli 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.Both Brotli library and nginx module are under active development.
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".
time-series database c-plus-plus tsdb time-series-database metrics
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