mzstd
Zstandard (RFC 8878) compression and decompression in safe Rust.
- Byte-identical encoder. For the same input and parameters,
single-threaded compression writes exactly the bytes of zstd 1.5.7:
one-shot calls match
ZSTD_compress2, and sessions matchZSTD_compressStream2driven with the same chunks, output capacities and flushes. This holds for levels -131072 to 22, the explicit compression parameters, long distance matching, checksums, content sizes, pledged sizes and size hints. - Independent decoder written from the format specification. It decodes every frame zstd writes apart from dictionary frames, with bounded window, input and output limits.
- Parallel compression with tasks you run on your own executor. Frames are valid Zstandard frames and are identical for any task count, but they are not byte-identical to zstd's multithreaded mode.
- No
unsafe, no dependencies on zstd. It runs withno_std+alloc, and there is a C ABI inmzstd-ffi.
[]
= "0.2"
Usage
use ;
let mut encoder = new?;
let compressed = encoder.compress?;
let restored = default.decompress?;
assert_eq!;
# Ok::
Explicit parameters override the level just as ZSTD_CCtx_setParameter does:
use ;
let config = default
.with_level
.with_checksum
.with_params
.with_long_distance_matching;
let mut encoder = new?;
# Ok::
Choose your API
Compression and decompression expose the same core I/O shapes. Pick the shape that
matches how your application already moves bytes. ParallelCompressor (in
mzstd::compressor::parallel) is a separate execution strategy for compression: it
splits one frame into independent segments and hands them to your executor as tasks,
either for a whole input at once or for input that arrives in chunks. It requires std.
| I/O shape | Compression | Decompression |
|---|---|---|
Return a new Vec<u8> |
Compressor::compress |
Decompressor::decompress |
| Append to an existing Vec | compress_into |
decompress_into |
| Write into a caller-owned slice | compress_to_slice, compress_to_uninit |
decompress_to_slice |
Pull output through std::io::Read |
Compressor::reader |
Decompressor::reader |
Push input through std::io::Write |
Compressor::writer |
Decompressor::writer |
| Drive input/output incrementally | start → EncoderSession |
start → DecoderSession |
| Same, with the session owning the codec | into_session → EncoderSessionOwned |
into_session → DecoderSessionOwned |
| Split one known input across your threads | ParallelCompressor::prepare_slice → ScopedParallelBatch |
— |
| Stream chunked input across your threads | ParallelCompressor::start → ParallelEncoderSession + ParallelTaskQueue |
— |
| Same, with the session owning the compressor | ParallelCompressor::into_session → ParallelEncoderSessionOwned |
— |
Push or pull through std::io across your threads |
ParallelCompressor::writer, ParallelCompressor::reader |
— |
Features
| Feature | Default | Enables |
|---|---|---|
compression |
yes | mzstd::compressor |
decompression |
yes | mzstd::decompressor |
std |
yes | std::error::Error, mzstd::io, parallel compression |
no_std |
no | alloc-only build; overrides std |
hotpath, hotpath-cpu, hotpath-alloc |
no | profiling anchors |
Performance
Our benchmarks
Compression writes byte-identical frames to zstd 1.5.7 and reaches about 1.000× its speed across the comparison corpus; decompression reaches 1.033×. These medians include empty and tiny inputs. Compressible text remains slower.
Recorded 2026-10-14 · Intel Core i7-13700KF · WSL2 · cold one-shot APIs. Each value is the median of per-dataset ratios across eight equally weighted datasets, including empty and tiny inputs. A speed ratio above 1× is faster than C; every frame is byte-identical to zstd's, so the size ratio is 1× at every level. The median over all 192 dataset/level pairs is 1.000×, with lower mean latency in 96 pairs. The margin does not establish an overall lead. Across levels, Alice text reaches a median 0.925× and cyclic Alice at 1 MiB 0.934×; empty, tiny and repeated-byte inputs are faster than C.
The benchmark includes compressor construction, allocation, compression, and disposal. Results apply to the recorded revision and machine.
Per-dataset results and methodology · Raw measurements · Reproduce the benchmarks
Recorded 2026-10-13 · Intel Core i7-13700KF · WSL2 · cold one-shot APIs. zstd C and mzstd decode identical C-written frames at source levels -5 to 22. All 384 cases restore the original bytes. mzstd runs at 1.03–1.04× C's speed at every source level (median 1.033× over all 192 pairs): much faster on empty and tiny frames, faster on random and run-length data, and 0.81–0.96× on compressible text. Construction, allocation, decode and disposal are timed; C reads the output capacity from the frame header.
Per-level and dataset results · Raw measurements · Methodology and limits
Verification
- Differential tests against zstd 1.5.7 (built from the vendored submodule by
zstd-ffi). They cover every level on a standard corpus, thousands of random advanced-parameter configurations, streaming schedules with flushes and wrapped windows, LDM, short destinations, and a build mode that forces index overflow correction on both sides. - Decoder tests: reference frames through every entry point, upstream's golden vectors, truncation and bit-flip corruption, limits.
- AFL++ targets in
fuzz/afl. Encoder targets: differential, output capacity, sessions, lifecycle, parallel and parameter parsing. Decoder targets: raw input against the reference decoder, chunked sessions, and reference-written frames. - 100% function coverage, checked with
cargo llvm-cov.
See architecture/ for how the code is organized
and verified.
Not supported
- Dictionaries
- Magicless frames
targetCBlockSize- External sequence producers
- Legacy (v0.x) frames
- Byte identity with zstd's multithreaded mode
License
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or https://opensource.org/licenses/MIT)
at your option. The encoder is a port of zstd, used under its BSD license; see NOTICE.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.