Comparison
aquila vs typesense
Verdict
Pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches; pick typesense if typesense is an open-source and type-tolerant fuzzy search engine written in C++, primarily suitable for applications requiring speedy search responses with high tolerance to typos.
Markdown twin · aquila alternatives · typesense alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | aquila | typesense |
|---|---|---|
| Maintenance | Dormant (817d since push) As of 3w · github_public_v1 | Very active (4d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 1d · 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
- aquila
- Efficient Neural Search Engine
- typesense
- Fast, typo tolerant, in-memory fuzzy Search Engine
Stars
- aquila
- 379
- typesense
- 26k
Forks
- aquila
- 26
- typesense
- 963
Open issues
- aquila
- 13
- typesense
- 872
Language
- aquila
- HTML
- typesense
- C++
Adopt for
- aquila
- Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
- typesense
- Typesense is an open-source and type-tolerant fuzzy search engine written in C++, primarily suitable for applications requiring speedy search responses with high tolerance to typos.
Persona
- aquila
- -
- typesense
- -
Runtime
- aquila
- -
- typesense
- -
License
- aquila
- -
- typesense
- GPL-3.0 License ensures typesense is free to use, modify and distribute as long as those changes are made available under the same licensing terms.
Last pushed
- aquila
- May 6, 2024
- typesense
- Aug 18, 2026
Categories
- aquila
- Data & Retrieval, Vector Databases
- typesense
- Data & Retrieval
Trust and health
Maintenance
- aquila
- Dormant (18%)
- typesense
- Very active (96%)
Days since push
- aquila
- 817d
- typesense
- 4d
Open issues (now)
- aquila
- 13
- typesense
- 872
Stars delta
- aquila
- Unknown
- typesense
- +128 (30d)
Open issues delta
- aquila
- Unknown
- typesense
- +20 (30d)
Full report
- aquila
- Trust report
- typesense
- Trust report
Choose aquila if…
- aquila is primarily HTML; typesense is C++.
- Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors.
- Also covers Vector Databases.
- 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
Choose typesense if…
- typesense is primarily C++; aquila is HTML.
- Self-hosting on-premises or in-cloud environments, enabling full control over data and infrastructure.
- Tags unique to typesense: algolia, datastore, elastic-search, faceting.
- When seeking a drop-in replacement or alternative for Algolia, especially if considering an open-source solution.
When NOT to use typesense
- If the project is working with a smaller dataset where setting up an additional service could be overkill and simplicity outweighs high performance.
- When the team prefers not to use GPL-3.0 licensed software, as this may pose limitations or requirements on how the code can be used or distributed.
- In projects requiring complex vector search functionalities that might need more than what Typesense offers in its current feature set.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (typesense/typesense) · observed Aug 23, 2026
- GitHub forks (typesense/typesense) · observed Aug 23, 2026
- Last push (typesense/typesense) · observed Aug 18, 2026
- License file (GPL-3.0) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: aquila 379 · typesense 26k (synced Aug 2, 2026).
Common questions
- What is the difference between aquila and typesense?
- aquila: Efficient Neural Search Engine. typesense: Fast, typo tolerant, in-memory fuzzy Search Engine. See the comparison table for live GitHub stats and shared categories.
- When should I choose aquila over typesense?
- Choose aquila over typesense when aquila is primarily HTML; typesense is C++; Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors; Also covers Vector Databases; 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 choose typesense over aquila?
- Choose typesense over aquila when typesense is primarily C++; aquila is HTML; Self-hosting on-premises or in-cloud environments, enabling full control over data and infrastructure; Tags unique to typesense: algolia, datastore, elastic-search, faceting; When seeking a drop-in replacement or alternative for Algolia, especially if considering an open-source solution.
- 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
- When should I avoid typesense?
- If the project is working with a smaller dataset where setting up an additional service could be overkill and simplicity outweighs high performance. When the team prefers not to use GPL-3.0 licensed software, as this may pose limitations or requirements on how the code can be used or distributed. In projects requiring complex vector search functionalities that might need more than what Typesense offers in its current feature set.
- Is aquila or typesense more popular on GitHub?
- typesense has more GitHub stars (26,475 vs 379). Stars measure visibility, not whether either tool fits your constraints.
- Are aquila and typesense open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to aquila or typesense?
- GraphCanon lists graph-backed alternatives at aquila alternatives and typesense alternatives (aquila markdown twin, typesense 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, aquila or typesense?
- aquila: Dormant. typesense: Very 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 aquila and typesense?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; typesense trust report.