LZAV is a fast general-purpose in-memory data compression algorithm based on now-classic LZ77 lossless data compression method. LZAV holds a good position on the Pareto landscape of factors, among many similar in-memory (non-streaming) compression algorithms.

LZAV algorithm's code is portable, cross-platform, scalar, header-only, inlineable C (C++ compatible). It supports big- and little-endian platforms, and any memory alignment models. The algorithm is efficient on both 32- and 64-bit platforms. Incompressible data expands by no more than 0.58%.

LZAV does not sacrifice internal out-of-bounds (OOB) checks for decompression speed. This means that LZAV can be used in strict conditions where OOB memory writes (and especially reads) that lead to a trap, are unacceptable (e.g., real-time, system, server software). LZAV can be safely used to decompress malformed or damaged compressed data. Which means that LZAV does not require calculation of a checksum (or hash) of the compressed data. Only a checksum of uncompressed data may be required, depending on application's guarantees.

The internal functions available in the lzav.h file allow you to easily implement, and experiment with, your own compression algorithms. LZAV stream format and decompressor have a potential of high decompression speeds and compression ratios, which depends on the way data is compressed.

To compress data:

#include "lzav.h"

int max_len = lzav_compress_bound( src_len );
void* comp_buf = malloc( max_len );
int comp_len = lzav_compress_default( src_buf, comp_buf, src_len, max_len );

if( comp_len == 0 && src_len != 0 )
{
    // Error handling.
}

To decompress data:

#include "lzav.h"

void* decomp_buf = malloc( src_len );
int l = lzav_decompress( comp_buf, decomp_buf, comp_len, src_len );

if( l < 0 )
{
    // Error handling.
}

To compress data with a higher ratio, for non-time-critical uses (e.g., compression of application's static assets):

#include "lzav.h"

int max_len = lzav_compress_bound_hi( src_len ); // Note another bound function!
void* comp_buf = malloc( max_len );
int comp_len = lzav_compress_hi( src_buf, comp_buf, src_len, max_len );

if( comp_len == 0 && src_len != 0 )
{
    // Error handling.
}

LZAV algorithm and its source code (which is ISO C99) were quality-tested with: Clang, GCC, MSVC, Intel C++ compilers; on x86, x86-64 (Intel, AMD), AArch64 (Apple Silicon) architectures; Windows 10, CentOS 8 Linux, macOS 14.3.

The tables below present performance ballpark numbers of LZAV algorithm (based on Silesia dataset).

While LZ4 there seems to be compressing faster, LZAV comparably provides 13.7% memory storage cost savings. This is a significant benefit in database and file system use cases since compression is only about 30% slower while CPUs rarely run at their maximum capacity anyway, and disk I/O times are reduced due to a better compression. In general, LZAV holds a very strong position in this class of data compression algorithms, if one considers all factors: compression and decompression speeds, compression ratio, and not less important - code maintainability: LZAV is maximally portable and has a rather small independent codebase.

Performance of LZAV is not limited to the presented ballpark numbers. Depending on the data being compressed, LZAV can achieve 800 MB/s compression and 4500 MB/s decompression speeds. Incompressible data decompresses at 10000 MB/s rate, which is not far from the "memcpy". There are cases like the enwik9 dataset where LZAV provides 20.7% higher memory storage savings compared to LZ4. However, on small data (below 50 KB), compression ratio difference between LZAV and LZ4 diminishes, and LZ4 may have some advantage.

LZAV algorithm's geomean performance on a variety of datasets is 530 +/- 150 MB/s compression and 3500 +/- 1200 MB/s decompression speeds, on 4+ GHz 64-bit processors released after 2019. Note that the algorithm exhibits adaptive qualities, and its actual performance depends on the data being compressed. LZAV may show an exceptional performance on your specific data.

It is also worth noting that compression methods like LZAV and LZ4 usually have an advantage over dictionary- and entropy-based coding in that hash-table-based compression has a very small overhead while the classic LZ77 decompression has none at all - this is especially relevant for smaller data.

For a more comprehensive in-memory compression algorithms benchmark you may visit lzbench.

Silesia compression corpus

Silesia compression corpus

Silesia compression corpus

P.S. Popular Zstd's benchmark was not included here, because it is not a pure LZ77, much harder to integrate, and has a much larger code size - a different league, close to zlib. Here are author's Zstd measurements with TurboBench, on Ryzen 3700X, on Silesia dataset:

1. LZAV API is not equivalent to LZ4 nor Snappy API. For example, the "dstl" parameter in the decompressor should specify the original uncompressed length, which should have been previously stored in some way, independent of LZAV.

2. Run-time memory sanitizers like Valgrind and Dr.Memory may generate the "uninitialized read" warning in decompressor's block type 1 handler. This is an expected behavior, and not a bug - this happens due to SIMD optimizations that read bytes from the output buffer (within its valid range) which were not yet initialized.

3. Compared to Clang, other compilers systematically produce 5% slower LZAV code. Compiler architecture tuning (other than generic x86-64) may produce varying, including counter-productive, results.

4. From a technical point of view, peak decompression speeds of LZAV have an implicit limitation arising from its more complex stream format compared to LZ4: LZAV decompression requires more code branching. Another limiting factor is a rather big 16 MiB LZ77 window which is not CPU cache-friendly. On the other hand, without these features it would not be possible to achieve competitive compression ratios while having fast compression speeds.

• Paul Dreik, for finding memcpy UB in the decompressor.