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Zstandard is a lossless data compression algorithm developed by Yann Collet at Facebook. Zstd is the corresponding reference implementation in C, released as open-source software on 31 August 2016.
Standards, Usage & Features
Explore the main themes, entities and connections around Zstd. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
compression zstandard algorithm also version support rfc 31 license ratio used faster decompression october added released august 2018 facebook 8478
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Zstd | Developers | Yann Collet, Nick Terrell, Przemysław Skibiński | 1.00 | infobox |
| Zstd | License | BSD-3-Clause or GPL-2.0-or-later (dual-licensed) | 1.00 | infobox |
| Zstd | Operating system | Cross-platform | 1.00 | infobox |
| Zstd | Original author | Yann Collet | 1.00 | infobox |
| Zstd | Platform | Portable | 1.00 | infobox |
| Zstd | Release | 23 January 2015 (2015-01-23) | 1.00 | infobox |
| Zstd | Repository | github.com/facebook/zstd | 1.00 | infobox |
| Zstd | Stable release | 1.5.7 / 20 February 2025; 18 months ago (20 February 2025) | 1.00 | infobox |
| Zstd | Type | Data compression | 1.00 | infobox |
| Zstd | Website | facebook.github.io/zstd/ | 1.00 | infobox |
| Zstd | Written in | C | 1.00 | infobox |
| Zstd | is a | corresponding reference implementation in C | 0.90 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.