lrzip
What it is
lrzip is a free, GPL-2.0 command-line compression utility for large files, usually above 10–50 MB. It first applies an extended rzip pass to reduce redundancy across distant file regions, then uses a selected backend: LZMA, ZPAQ, LZO, GZIP, BZIP2, or no further compression. Users can favor speed or smaller output, but not both simultaneously. Compression and decompression are heavily multithreaded, with CPU detection built in. The program uses available RAM for compression windows; sliding mmap can use windows larger than RAM but may be extremely slow. Encryption defaults to AES-256-GCM with PBKDF2-HMAC-SHA512 and HKDF, and lost passwords cannot be recovered. The main utility handles single files, while lrztar packages directories. It targets 64-bit Unix-like systems and supports macOS 10.5 or later from version 0.43. Building from source uses configure and make, with releases on GitHub.
For and against
For
- Multiple compression backends
- Multithreaded compression and decompression
- Optional AES-256-GCM encryption
- lrztar packages directories
- Free GPL-2.0 license
Against
- Speed and smallest size cannot be optimized together
- Compression needs substantial memory
- Sliding mmap mode can be extremely slow
- Forgotten encryption passwords cannot be recovered
The verdict
lrzip offers long-range preprocessing, several backends, multithreading, and encryption for large-file archives. Its command-line workflow and resource demands make system capacity and Unix-like platforms important considerations.
Who it suits
lrzip suits users compressing large individual files or directories through Unix-like command-line tools. It is relevant to people who can provide substantial memory and modern processor capacity.
Plans and prices
lrzip
GPL-2.0 licensed compression utility
Read 9 Oct 2026 · github.com
On the record
- Compression backends
- Available backends include LZMA, ZPAQ, LZO, GZIP, BZIP2, and an option to leave data uncompressed after rzip preparation.github.com · read 9 Oct 2026
- Downloads and installation
- The project README points to GitHub releases for stable source tarballs and documents building from source with configure and make.github.com · read 9 Oct 2026
- Encryption
- The README says the default encryption option uses AES-256-GCM with PBKDF2-HMAC-SHA512 and HKDF, and forgotten passwords cannot be recovered.github.com · read 9 Oct 2026
- File handling limit
- The main lrzip program works on single files; the lrztar wrapper can package directories for compression.github.com · read 9 Oct 2026
- Integrity check
- The README's example decompression command uses an integrity check before decompressing.github.com · read 9 Oct 2026
- Large-file memory use
- lrzip uses available RAM for compression windows and offers a sliding mmap mode that can use windows larger than RAM, though this can be extremely slow.github.com · read 9 Oct 2026
- License and support
- The repository lists a GPL-2.0 license and directs users to GitHub Issues to report bugs.github.com · read 9 Oct 2026
- Long-range reduction
- It uses an extended version of rzip for a first pass that reduces long-distance redundancy before compression.github.com · read 9 Oct 2026
- macOS support
- The FAQ says version 0.43 and later should build on Mac OS X 10.5 or later.github.com · read 9 Oct 2026
- Parallel processing
- The README says lrzip is heavily multithreaded for backend compression and decompression and detects the number of CPUs to use.github.com · read 9 Oct 2026
- Platform requirement
- lrzip targets 64-bit platforms and the build guide calls for an operating system with typical Unix headers and libraries.github.com · read 9 Oct 2026
- Purpose
- lrzip is a compression utility designed to compress large files, usually larger than 10–50 MB.github.com · read 9 Oct 2026
- Resource considerations
- The README says compression needs substantial memory and a modern processor for best performance, and warns against production server use without CPU and RAM limits.github.com · read 9 Oct 2026
- Speed and size
- The README says users can optimize for compression speed or output size, but not both at once.github.com · read 9 Oct 2026
