Home/Compare/examples vs recipes

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 today

examples logo

examples

pinecone-io/examples

3.0kpushed Aug 14, 2026
vs
recipes logo

recipes

weaviate/recipes

944pushed Aug 13, 2026

Trust & integrity

Signalexamplesrecipes
Maintenance
Very active (0d since push)
As of 6d · github_public_v1
Active (8d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 6d · 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

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
944

Forks

examples
1.1k
recipes
197

Open issues

examples
61
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
Aug 14, 2026
recipes
Aug 13, 2026

Categories

examples
Data & Retrieval, Vector Databases
recipes
Data & Retrieval, Vector Databases

Trust and health

Maintenance

examples
Very active (96%)
recipes
Active (82%)

Days since push

examples
0d
recipes
8d

Open issues (now)

examples
61
recipes
4

Stars delta

examples
+8 (30d)
recipes
+3 (30d)

Open issues delta

examples
-3 (30d)
recipes
-2 (30d)

Full report

examples
Trust report

Typed relationship

examples related 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 on cards: examples 3.0k · recipes 944 (synced Aug 15, 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 (3,036 vs 944). 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: 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.

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