Comparison
aquila vs recipes
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 recipes if comprehensive notebooks covering Weaviate features including vector search, media search, multi-tenancy configurations and integration use cases.
Markdown twin · aquila alternatives · recipes alternatives
GraphCanon updated today
Trust & integrity
| Signal | aquila | recipes |
|---|---|---|
| Maintenance | Dormant (817d since push) As of 2w · github_public_v1 | Active (8d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of today · 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
- recipes
- End-to-end notebooks for using Weaviate features and integrations.
Stars
- aquila
- 379
- recipes
- 944
Forks
- aquila
- 26
- recipes
- 197
Open issues
- aquila
- 13
- recipes
- 4
Language
- aquila
- HTML
- recipes
- Jupyter Notebook
Adopt for
- aquila
- Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
- recipes
- Comprehensive notebooks covering Weaviate features including vector search, media search, multi-tenancy configurations and integration use cases.
Persona
- aquila
- -
- recipes
- -
Runtime
- aquila
- -
- recipes
- -
License
- aquila
- -
- recipes
- -
Last pushed
- aquila
- May 6, 2024
- recipes
- Aug 13, 2026
Categories
- aquila
- Data & Retrieval, Vector Databases
- recipes
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- aquila
- Dormant (18%)
- recipes
- Active (82%)
Days since push
- aquila
- 817d
- recipes
- 8d
Open issues (now)
- aquila
- 13
- recipes
- 4
Stars delta
- aquila
- Unknown
- recipes
- +3 (30d)
Open issues delta
- aquila
- Unknown
- recipes
- -2 (30d)
Full report
- aquila
- Trust report
- recipes
- Trust report
Choose aquila if…
- aquila is primarily HTML; recipes is Jupyter Notebook.
- 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
Choose recipes if…
- recipes is primarily Jupyter Notebook; aquila is HTML.
- Tags unique to recipes: function-calling, generative-ai, llm frameworks, python.
- When you are specifically interested in exploring various integrations with cloud hyperscalers (Google, AWS), LLM frameworks (LangChain, LlamaIndex), and other technologies mentioned, such as Databri
When NOT to use recipes
- If you are looking for generalized vector database use case examples that do not specifically showcase Weaviate's unique integrations or features
- When your focus is on understanding and using broad category services instead of the specific, detailed examples and configurations available in the Weaviate ecosystem
- For cases where a competitor tool offers better support for other specific needs, such as more comprehensive integration with data platforms not specifically covered by Weaviate like MongoDB or Redis
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 (weaviate/recipes) · observed Aug 21, 2026
- GitHub forks (weaviate/recipes) · observed Aug 21, 2026
- Last push (weaviate/recipes) · observed Aug 13, 2026
- License file (unknown) · observed Aug 21, 2026
- Decision facts (enrichment) · observed Jul 9, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: aquila 379 · recipes 944 (synced Aug 2, 2026).
Common questions
- What is the difference between aquila and recipes?
- aquila: Efficient Neural Search Engine. recipes: End-to-end notebooks for using Weaviate features and integrations.. See the comparison table for live GitHub stats and shared categories.
- When should I choose aquila over recipes?
- Choose aquila over recipes when aquila is primarily HTML; recipes is Jupyter Notebook; 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 choose recipes over aquila?
- Choose recipes over aquila when recipes is primarily Jupyter Notebook; aquila is HTML; Tags unique to recipes: function-calling, generative-ai, llm frameworks, python; When you are specifically interested in exploring various integrations with cloud hyperscalers (Google, AWS), LLM frameworks (LangChain, LlamaIndex), and other technologies mentioned, such as Databri.
- 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 recipes?
- If you are looking for generalized vector database use case examples that do not specifically showcase Weaviate's unique integrations or features When your focus is on understanding and using broad category services instead of the specific, detailed examples and configurations available in the Weaviate ecosystem For cases where a competitor tool offers better support for other specific needs, such as more comprehensive integration with data platforms not specifically covered by Weaviate like MongoDB or Redis
- Is aquila or recipes more popular on GitHub?
- recipes has more GitHub stars (944 vs 379). Stars measure visibility, not whether either tool fits your constraints.
- Are aquila and recipes open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to aquila or recipes?
- GraphCanon lists graph-backed alternatives at aquila alternatives and recipes alternatives (aquila markdown twin, recipes 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 recipes?
- aquila: Dormant. recipes: 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 recipes?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; recipes trust report.