Comparison
aquila vs rag-fusion
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 rag-fusion if rAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.
Markdown twin · aquila alternatives · rag-fusion alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | aquila | rag-fusion |
|---|---|---|
| Maintenance | Dormant (817d since push) As of 3w · github_public_v1 | Slowing (118d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal 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
- rag-fusion
- multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation
Stars
- aquila
- 379
- rag-fusion
- 952
Forks
- aquila
- 26
- rag-fusion
- 115
Open issues
- aquila
- 13
- rag-fusion
- 0
Language
- aquila
- HTML
- rag-fusion
- Python
Adopt for
- aquila
- Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
- rag-fusion
- RAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.
Persona
- aquila
- -
- rag-fusion
- -
Runtime
- aquila
- -
- rag-fusion
- -
License
- aquila
- -
- rag-fusion
- MIT
Last pushed
- aquila
- May 6, 2024
- rag-fusion
- Apr 26, 2026
Categories
- aquila
- Data & Retrieval, Vector Databases
- rag-fusion
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- aquila
- Dormant (18%)
- rag-fusion
- Slowing (36%)
Days since push
- aquila
- 817d
- rag-fusion
- 118d
Open issues (now)
- aquila
- 13
- rag-fusion
- 0
Stars delta
- aquila
- Unknown
- rag-fusion
- +6 (30d)
Open issues delta
- aquila
- Unknown
- rag-fusion
- 0 (30d)
Owner type
- aquila
- Organization
- rag-fusion
- User
Full report
- aquila
- Trust report
- rag-fusion
- Trust report
Choose aquila if…
- aquila is primarily HTML; rag-fusion is Python.
- 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 rag-fusion if…
- rag-fusion is primarily Python; aquila is HTML.
- Tags unique to rag-fusion: chromadb, openai, python, rag-fusion.
- Also covers Evaluation & Observability.
- For enhancing precision in retrieval-augmented generation tasks needing complex query processing
When NOT to use rag-fusion
- If you require real-time performance, as multi-query generation may introduce latency
- In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques
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 (Raudaschl/rag-fusion) · observed Aug 23, 2026
- GitHub forks (Raudaschl/rag-fusion) · observed Aug 23, 2026
- Last push (Raudaschl/rag-fusion) · observed Apr 26, 2026
- License file (MIT) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: aquila 379 · rag-fusion 952 (synced Aug 2, 2026).
Common questions
- What is the difference between aquila and rag-fusion?
- aquila: Efficient Neural Search Engine. rag-fusion: multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation. See the comparison table for live GitHub stats and shared categories.
- When should I choose aquila over rag-fusion?
- Choose aquila over rag-fusion when aquila is primarily HTML; rag-fusion is Python; 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 rag-fusion over aquila?
- Choose rag-fusion over aquila when rag-fusion is primarily Python; aquila is HTML; Tags unique to rag-fusion: chromadb, openai, python, rag-fusion; Also covers Evaluation & Observability; For enhancing precision in retrieval-augmented generation tasks needing complex query 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
- When should I avoid rag-fusion?
- If you require real-time performance, as multi-query generation may introduce latency In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques
- Is aquila or rag-fusion more popular on GitHub?
- rag-fusion has more GitHub stars (952 vs 379). Stars measure visibility, not whether either tool fits your constraints.
- Are aquila and rag-fusion open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to aquila or rag-fusion?
- GraphCanon lists graph-backed alternatives at aquila alternatives and rag-fusion alternatives (aquila markdown twin, rag-fusion 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 rag-fusion?
- aquila: Dormant. rag-fusion: 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 rag-fusion?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; rag-fusion trust report.