Comparison
meilisearch vs fastembed
Verdict
Pick meilisearch when meilisearch is primarily Rust; fastembed is Python; pick fastembed when fastembed is primarily Python; meilisearch is Rust.
Markdown twin · meilisearch alternatives · fastembed alternatives
GraphCanon updated today
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Trust & integrity
| Signal | meilisearch | fastembed |
|---|---|---|
| Maintenance | Very active (1d since push) As of today · github_public_v1 | Active (18d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- meilisearch
- A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
- fastembed
- Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Stars
- meilisearch
- 58k
- fastembed
- 3.1k
Forks
- meilisearch
- 2.6k
- fastembed
- 213
Open issues
- meilisearch
- 310
- fastembed
- 137
Language
- meilisearch
- Rust
- fastembed
- Python
Adopt for
- meilisearch
- Meilisearch is a Rust-based, lightning-fast hybrid search engine that integrates easily into web and mobile applications. It supports both full-text and vector searches.
- fastembed
- -
Persona
- meilisearch
- -
- fastembed
- -
Runtime
- meilisearch
- -
- fastembed
- -
License
- meilisearch
- Other
- fastembed
- Apache-2.0
Last pushed
- meilisearch
- Jul 9, 2026
- fastembed
- Jun 23, 2026
Categories
- meilisearch
- Vector Databases, Data & Retrieval
- fastembed
- LLM Frameworks, Data & Retrieval, Vector Databases
Trust and health
Maintenance
- meilisearch
- Very active (96%)
- fastembed
- Active (82%)
Days since push
- meilisearch
- 1d
- fastembed
- 18d
Open issues (now)
- meilisearch
- 310
- fastembed
- 137
Full report
- meilisearch
- Trust report
- fastembed
- Trust report
Choose meilisearch if…
- meilisearch is primarily Rust; fastembed is Python.
- License: meilisearch is Other, fastembed is Apache-2.0.
- Tags unique to meilisearch: app-search, full-text-search, ai, enterprise-search.
- meilisearch ships Docker support for self-hosted deployment.
- - You require fast integration capabilities for your web or mobile application, as Meilisearch offers flexible deployment options.
When NOT to use meilisearch
- - When you specifically need language support for a large number of languages beyond what Meilisearch currently offers, as some specialized multilingual search engines might handle more languages nimb
- - If your application does not require real-time search-as-you-type or typo tolerance features which can add overhead and may slow down performance in less demanding scenarios.
Choose fastembed if…
- fastembed is primarily Python; meilisearch is Rust.
- License: fastembed is Apache-2.0, meilisearch is Other.
- Tags unique to fastembed: embeddings, python, rag, retrieval-augmented-generation.
- Also covers LLM Frameworks.
When NOT to use fastembed
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (meilisearch/meilisearch) · observed Jul 11, 2026
- GitHub forks (meilisearch/meilisearch) · observed Jul 11, 2026
- Last push (meilisearch/meilisearch) · observed Jul 9, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (qdrant/fastembed) · observed Jul 11, 2026
- GitHub forks (qdrant/fastembed) · observed Jul 11, 2026
- Last push (qdrant/fastembed) · observed Jun 23, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: meilisearch 58k · fastembed 3.1k (synced Jul 11, 2026).
Common questions
- What is the difference between meilisearch and fastembed?
- meilisearch: A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.. fastembed: Fast, Accurate, Lightweight Python library to make State of the Art Embedding. See the comparison table for live GitHub stats and shared categories.
- When should I choose meilisearch over fastembed?
- Choose meilisearch over fastembed when meilisearch is primarily Rust; fastembed is Python; License: meilisearch is Other, fastembed is Apache-2.0; Tags unique to meilisearch: app-search, full-text-search, ai, enterprise-search; meilisearch ships Docker support for self-hosted deployment; - You require fast integration capabilities for your web or mobile application, as Meilisearch offers flexible deployment options.
- When should I choose fastembed over meilisearch?
- Choose fastembed over meilisearch when fastembed is primarily Python; meilisearch is Rust; License: fastembed is Apache-2.0, meilisearch is Other; Tags unique to fastembed: embeddings, python, rag, retrieval-augmented-generation; Also covers LLM Frameworks.
- When should I avoid meilisearch?
- - When you specifically need language support for a large number of languages beyond what Meilisearch currently offers, as some specialized multilingual search engines might handle more languages nimb - If your application does not require real-time search-as-you-type or typo tolerance features which can add overhead and may slow down performance in less demanding scenarios.
- When should I avoid fastembed?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is meilisearch or fastembed more popular on GitHub?
- meilisearch has more GitHub stars (58,493 vs 3,085). Stars measure visibility, not whether either tool fits your constraints.
- Are meilisearch and fastembed open source?
- Yes - both are open-source projects on GitHub (meilisearch: Other, fastembed: Apache-2.0).
- Where can I find alternatives to meilisearch or fastembed?
- GraphCanon lists graph-backed alternatives at meilisearch alternatives and fastembed alternatives (meilisearch markdown twin, fastembed markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, meilisearch or fastembed?
- meilisearch: Very active. fastembed: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for meilisearch and fastembed?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: meilisearch trust report; fastembed trust report.