Comparison
aquila vs ragtune
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 ragtune if ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer.
Markdown twin · aquila alternatives · ragtune alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | aquila | ragtune |
|---|---|---|
| Maintenance | Dormant (817d since push) As of 3w · github_public_v1 | Slowing (129d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- ragtune
- Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers
Stars
- aquila
- 379
- ragtune
- 13
Forks
- aquila
- 26
- ragtune
- 1
Open issues
- aquila
- 13
- ragtune
- 0
Language
- aquila
- HTML
- ragtune
- Go
Adopt for
- aquila
- Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
- ragtune
- Ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer.
Persona
- aquila
- -
- ragtune
- -
Runtime
- aquila
- -
- ragtune
- -
License
- aquila
- -
- ragtune
- MIT
Last pushed
- aquila
- May 6, 2024
- ragtune
- Mar 25, 2026
Categories
- aquila
- Data & Retrieval, Vector Databases
- ragtune
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- aquila
- Dormant (18%)
- ragtune
- Slowing (36%)
Days since push
- aquila
- 817d
- ragtune
- 129d
Open issues (now)
- aquila
- 13
- ragtune
- 0
Owner type
- aquila
- Organization
- ragtune
- User
OSV dependency advisories
- aquila
- No lockfile (source not queried)
- ragtune
- Published findings
Full report
- aquila
- Trust report
- ragtune
- Trust report
Choose aquila if…
- aquila is primarily HTML; ragtune is Go.
- 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 ragtune if…
- ragtune is primarily Go; aquila is HTML.
- Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation.
- Also covers Evaluation & Observability.
- For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly.
When NOT to use ragtune
- If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort.
- When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.
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 (metawake/ragtune) · observed Aug 2, 2026
- GitHub forks (metawake/ragtune) · observed Aug 2, 2026
- Last push (metawake/ragtune) · observed Mar 25, 2026
- License file (MIT) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: aquila 379 · ragtune 13 (synced Aug 2, 2026).
Common questions
- What is the difference between aquila and ragtune?
- aquila: Efficient Neural Search Engine. ragtune: Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers. See the comparison table for live GitHub stats and shared categories.
- When should I choose aquila over ragtune?
- Choose aquila over ragtune when aquila is primarily HTML; ragtune is Go; 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 ragtune over aquila?
- Choose ragtune over aquila when ragtune is primarily Go; aquila is HTML; Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation; Also covers Evaluation & Observability; For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly.
- 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 ragtune?
- If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort. When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.
- Is aquila or ragtune more popular on GitHub?
- aquila has more GitHub stars (379 vs 13). Stars measure visibility, not whether either tool fits your constraints.
- Are aquila and ragtune open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to aquila or ragtune?
- GraphCanon lists graph-backed alternatives at aquila alternatives and ragtune alternatives (aquila markdown twin, ragtune 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 ragtune?
- aquila: Dormant. ragtune: Slowing. 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 ragtune?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; ragtune trust report.