Comparison
aquila vs examples
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 examples if examples, powered by Pinecone vector databases, offers interactive Jupyter Notebooks to aid users in experimenting with semantic search tasks through hands-on guidance.
Markdown twin · aquila alternatives · examples alternatives
GraphCanon updated 5d
vs
Trust & integrity
| Signal | aquila | examples |
|---|---|---|
| Maintenance | Dormant (817d since push) As of 2w · github_public_v1 | Very active (0d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 5d · 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
- examples
- Jupyter Notebooks to help you get hands-on with Pinecone vector databases
Stars
- aquila
- 379
- examples
- 3.0k
Forks
- aquila
- 26
- examples
- 1.1k
Open issues
- aquila
- 13
- examples
- 61
Language
- aquila
- HTML
- examples
- 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.
- examples
- Examples, powered by Pinecone vector databases, offers interactive Jupyter Notebooks to aid users in experimenting with semantic search tasks through hands-on guidance.
Persona
- aquila
- -
- examples
- -
Runtime
- aquila
- -
- examples
- -
License
- aquila
- -
- examples
- MIT
Last pushed
- aquila
- May 6, 2024
- examples
- Aug 14, 2026
Categories
- aquila
- Data & Retrieval, Vector Databases
- examples
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- aquila
- Dormant (18%)
- examples
- Very active (96%)
Days since push
- aquila
- 817d
- examples
- 0d
Open issues (now)
- aquila
- 13
- examples
- 61
Stars delta
- aquila
- Unknown
- examples
- +8 (30d)
Open issues delta
- aquila
- Unknown
- examples
- -3 (30d)
Full report
- aquila
- Trust report
- examples
- Trust report
Choose aquila if…
- aquila is primarily HTML; examples 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 examples if…
- examples is primarily Jupyter Notebook; aquila is HTML.
- Tags unique to examples: ai, jupyter-notebook, llm, python.
- When you need specific examples and walkthroughs for working with Pinecone's vector database technology using interactive Jupyter Notebooks.
When NOT to use examples
- Avoid if you're looking for generic tools applicable to a wide range of vector databases; this repository focuses exclusively on Pinecone.
- Not ideal if you prefer starting with theoretical understanding before practical application; the provided guidance is geared toward immediate experimentation in Google Colab.
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 (pinecone-io/examples) · observed Aug 15, 2026
- GitHub forks (pinecone-io/examples) · observed Aug 15, 2026
- Last push (pinecone-io/examples) · observed Aug 14, 2026
- License file (MIT) · observed Aug 15, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: aquila 379 · examples 3.0k (synced Aug 2, 2026).
Common questions
- What is the difference between aquila and examples?
- aquila: Efficient Neural Search Engine. examples: Jupyter Notebooks to help you get hands-on with Pinecone vector databases. See the comparison table for live GitHub stats and shared categories.
- When should I choose aquila over examples?
- Choose aquila over examples when aquila is primarily HTML; examples 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 examples over aquila?
- Choose examples over aquila when examples is primarily Jupyter Notebook; aquila is HTML; Tags unique to examples: ai, jupyter-notebook, llm, python; When you need specific examples and walkthroughs for working with Pinecone's vector database technology using interactive Jupyter Notebooks.
- 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 examples?
- Avoid if you're looking for generic tools applicable to a wide range of vector databases; this repository focuses exclusively on Pinecone. Not ideal if you prefer starting with theoretical understanding before practical application; the provided guidance is geared toward immediate experimentation in Google Colab.
- Is aquila or examples more popular on GitHub?
- examples has more GitHub stars (3,036 vs 379). Stars measure visibility, not whether either tool fits your constraints.
- Are aquila and examples open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to aquila or examples?
- GraphCanon lists graph-backed alternatives at aquila alternatives and examples alternatives (aquila markdown twin, examples 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 examples?
- aquila: Dormant. examples: 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 examples?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; examples trust report.