Comparison
examples vs recipes
Verdict
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; pick recipes if comprehensive notebooks covering Weaviate features including vector search, media search, multi-tenancy configurations and integration use cases.
Markdown twin · examples alternatives · recipes alternatives
GraphCanon updated Sep 20, 2026
12views this month
vs
Trust & integrity
| Signal | examples | recipes |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Very active (3d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- examples
- Jupyter Notebooks to help you get hands-on with Pinecone vector databases
- recipes
- End-to-end notebooks for using Weaviate features and integrations.
Stars
- examples
- 3.0k
- recipes
- 947
Forks
- examples
- 1.1k
- recipes
- 198
Open issues
- examples
- 66
- recipes
- 4
Language
- examples
- Jupyter Notebook
- recipes
- Jupyter Notebook
Adopt for
- examples
- Examples, powered by Pinecone vector databases, offers interactive Jupyter Notebooks to aid users in experimenting with semantic search tasks through hands-on guidance.
- recipes
- Comprehensive notebooks covering Weaviate features including vector search, media search, multi-tenancy configurations and integration use cases.
Persona
- examples
- -
- recipes
- -
Runtime
- examples
- -
- recipes
- -
License
- examples
- MIT
- recipes
- -
Last pushed
- examples
- Sep 19, 2026
- recipes
- Sep 16, 2026
Categories
- examples
- Data & Retrieval, Vector Databases
- recipes
- Data & Retrieval, Vector Databases
Trust and health
Days since push
- examples
- 1d
- recipes
- 3d
Open issues (now)
- examples
- 66
- recipes
- 4
Stars delta
- examples
- +7 (30d)
- recipes
- +6 (30d)
Open issues delta
- examples
- +5 (30d)
- recipes
- -2 (30d)
Full report
- examples
- Trust report
- recipes
- Trust report
Typed relationship
examples recipesThese repos both offer end-to-end notebooks targeting the use of their respective database systems (Pinecone and Weaviate) in AI workloads.
Choose examples if…
- These repos both offer end-to-end notebooks targeting the use of their respective database systems (Pinecone and Weaviate) in AI workloads.
- Tags unique to examples: ai, jupyter-notebook, llm, semantic-search.
- 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.
Choose recipes if…
- These repos both offer end-to-end notebooks targeting the use of their respective database systems (Pinecone and Weaviate) in AI workloads.
- Tags unique to recipes: function-calling, generative-ai, llm frameworks, retrieval-augmented generation.
- 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 (pinecone-io/examples) · observed Sep 20, 2026
- GitHub forks (pinecone-io/examples) · observed Sep 20, 2026
- Last push (pinecone-io/examples) · observed Sep 19, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (weaviate/recipes) · observed Sep 20, 2026
- GitHub forks (weaviate/recipes) · observed Sep 20, 2026
- Last push (weaviate/recipes) · observed Sep 16, 2026
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 9, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: examples 3.0k · recipes 947 (synced Sep 20, 2026).
Common questions
- What is the difference between examples and recipes?
- examples: Jupyter Notebooks to help you get hands-on with Pinecone vector databases. 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 examples over recipes?
- Choose examples over recipes when These repos both offer end-to-end notebooks targeting the use of their respective database systems (Pinecone and Weaviate) in AI workloads; Tags unique to examples: ai, jupyter-notebook, llm, semantic-search; When you need specific examples and walkthroughs for working with Pinecone's vector database technology using interactive Jupyter Notebooks.
- When should I choose recipes over examples?
- Choose recipes over examples when These repos both offer end-to-end notebooks targeting the use of their respective database systems (Pinecone and Weaviate) in AI workloads; Tags unique to recipes: function-calling, generative-ai, llm frameworks, retrieval-augmented generation; 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 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.
- 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 examples or recipes more popular on GitHub?
- examples has more GitHub stars (3,043 vs 947). Stars measure visibility, not whether either tool fits your constraints.
- Are examples and recipes open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to examples or recipes?
- GraphCanon lists graph-backed alternatives at examples alternatives and recipes alternatives (examples 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, examples or recipes?
- examples: Very active. recipes: 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 examples and recipes?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: examples trust report; recipes trust report.