Comparison
fastembed-rs vs aquila
Verdict
Pick fastembed-rs if fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes; pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
Markdown twin · fastembed-rs alternatives · aquila alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | fastembed-rs | aquila |
|---|---|---|
| Maintenance | Very active (6d since push) As of 3d · github_public_v1 | Dormant (817d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3d · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- fastembed-rs
- Rust library for generating vector embeddings and reranking locally.
- aquila
- Efficient Neural Search Engine
Stars
- fastembed-rs
- 992
- aquila
- 379
Forks
- fastembed-rs
- 136
- aquila
- 26
Open issues
- fastembed-rs
- 1
- aquila
- 13
Language
- fastembed-rs
- Rust
- aquila
- HTML
Adopt for
- fastembed-rs
- fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes.
- aquila
- Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
Persona
- fastembed-rs
- -
- aquila
- -
Runtime
- fastembed-rs
- -
- aquila
- -
License
- fastembed-rs
- Apache-2.0
- aquila
- -
Last pushed
- fastembed-rs
- Aug 16, 2026
- aquila
- May 6, 2024
Categories
- fastembed-rs
- Data & Retrieval, Vector Databases
- aquila
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- fastembed-rs
- Very active (96%)
- aquila
- Dormant (18%)
Days since push
- fastembed-rs
- 6d
- aquila
- 817d
Open issues (now)
- fastembed-rs
- 1
- aquila
- 13
Stars delta
- fastembed-rs
- +20 (30d)
- aquila
- Unknown
Open issues delta
- fastembed-rs
- -2 (30d)
- aquila
- Unknown
Owner type
- fastembed-rs
- User
- aquila
- Organization
Full report
- fastembed-rs
- Trust report
- aquila
- Trust report
Choose fastembed-rs if…
- fastembed-rs is primarily Rust; aquila is HTML.
- Tags unique to fastembed-rs: embeddings, fastembed, rag, reranker.
- When you seek high-performance embedding generation within an application written in Rust.
When NOT to use fastembed-rs
- Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages.
- Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing.
Choose aquila if…
- aquila is primarily HTML; fastembed-rs is Rust.
- Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors.
- When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary
When NOT to use aquila
- If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration
- In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Anush008/fastembed-rs) · observed Aug 22, 2026
- GitHub forks (Anush008/fastembed-rs) · observed Aug 22, 2026
- Last push (Anush008/fastembed-rs) · observed Aug 16, 2026
- License file (Apache-2.0) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Aquila-Network/aquila) · observed Aug 2, 2026
- GitHub forks (Aquila-Network/aquila) · observed Aug 2, 2026
- Last push (Aquila-Network/aquila) · observed May 6, 2024
- License file (unknown) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: fastembed-rs 992 · aquila 379 (synced Aug 22, 2026).
Common questions
- What is the difference between fastembed-rs and aquila?
- fastembed-rs: Rust library for generating vector embeddings and reranking locally.. aquila: Efficient Neural Search Engine. See the comparison table for live GitHub stats and shared categories.
- When should I choose fastembed-rs over aquila?
- Choose fastembed-rs over aquila when fastembed-rs is primarily Rust; aquila is HTML; Tags unique to fastembed-rs: embeddings, fastembed, rag, reranker; When you seek high-performance embedding generation within an application written in Rust.
- When should I choose aquila over fastembed-rs?
- Choose aquila over fastembed-rs when aquila is primarily HTML; fastembed-rs is Rust; Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors; When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary.
- When should I avoid fastembed-rs?
- Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages. Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing.
- When should I avoid aquila?
- If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide
- Is fastembed-rs or aquila more popular on GitHub?
- fastembed-rs has more GitHub stars (992 vs 379). Stars measure visibility, not whether either tool fits your constraints.
- Are fastembed-rs and aquila open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to fastembed-rs or aquila?
- GraphCanon lists graph-backed alternatives at fastembed-rs alternatives and aquila alternatives (fastembed-rs markdown twin, aquila 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, fastembed-rs or aquila?
- fastembed-rs: Very active. aquila: Dormant. 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 fastembed-rs and aquila?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: fastembed-rs trust report; aquila trust report.