# antirez/smaz

Small strings compression library

Repository: https://github.com/antirez/smaz
Canonical: https://ross.abutalabs.com/products/smaz
Language: C
License: BSD-3-Clause
License Family: permissive
Last push: 2019-10-25T15:29:28+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 6364, "days_push": 2504, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1221, forks 133 (observed 2026-08-28T04:04:02.133795+00:00)

## What it is
Smaz is a small C compression library specialized for compressing very short strings, where general-purpose compressors like zlib fail. It compresses English text by 40-50% on average and can shrink even 2-3 byte strings.

## Use cases
- compress short strings for storage or transmission
- shrink URLs before storing them in a database
- reduce memory of small text keys in embedded systems
- compress text too short for zlib to help
- store compact English phrases in constrained memory

## When to choose
- you need to compress strings of a few bytes to a few dozen bytes
- your data is mostly lowercase English text or URLs
- you want a tiny dependency-free C library with a two-function API

## When to avoid
- you need general-purpose compression of large files or binary data
- your strings contain lots of numbers or random data
- you need maximum compression ratios on long documents

## Facets
- artifact type: library
- maturity: maintenance
- function: compression
- domain: developer-tools
- platform: cross-platform, c
- tags: short-strings, text-compression, embedded-friendly, algorithms

## Member repositories
- antirez/smaz (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:02.133795+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:15:40.443111+00:00, confidence not recorded.
  - readme: https://github.com/antirez/smaz (fetched 2026-08-28T04:04:02.133795+00:00, sha cf35bb79a02c)
- Data as of 2026-08-30T08:39:29.467469+00:00.