Comparison
cuvs vs examples
Verdict
Pick cuvs if cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering; 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 · cuvs alternatives · examples alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | cuvs | examples |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 | Very active (1d 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
- cuvs
- A library for vector search and clustering on the GPU
- examples
- Jupyter Notebooks to help you get hands-on with Pinecone vector databases
Stars
- cuvs
- 854
- examples
- 3.0k
Forks
- cuvs
- 236
- examples
- 1.1k
Open issues
- cuvs
- 738
- examples
- 66
Language
- cuvs
- Cuda
- examples
- Jupyter Notebook
Adopt for
- cuvs
- cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering.
- 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
- cuvs
- -
- examples
- -
Runtime
- cuvs
- -
- examples
- -
License
- cuvs
- Apache-2.0
- examples
- MIT
Last pushed
- cuvs
- Sep 20, 2026
- examples
- Sep 19, 2026
Categories
- cuvs
- Vector Databases
- examples
- Data & Retrieval, Vector Databases
Trust and health
Days since push
- cuvs
- 0d
- examples
- 1d
Open issues (now)
- cuvs
- 738
- examples
- 66
Stars delta
- cuvs
- +33 (30d)
- examples
- +7 (30d)
Open issues delta
- cuvs
- +93 (30d)
- examples
- +5 (30d)
Full report
- cuvs
- Trust report
- examples
- Trust report
Choose cuvs if…
- cuvs is primarily Cuda; examples is Jupyter Notebook.
- License: cuvs is Apache-2.0, examples is MIT.
- Tags unique to cuvs: anns, clustering, cuda, gpu.
- cuvs ships Docker support for self-hosted deployment.
- - When you need high-performance vector operations leveraging the parallel processing power of GPUs, specifically with CUDA.
When NOT to use cuvs
- - For environments where GPU resources are limited or unavailable because cuVS heavily relies on CUDA's capabilities for performance gains.
- - When you prioritize portability across different hardware, as cuVS being tied to CUDA means it may not be optimal on non-NVIDIA GPUs or CPU-only systems.
Choose examples if…
- examples is primarily Jupyter Notebook; cuvs is Cuda.
- License: examples is MIT, cuvs is Apache-2.0.
- Tags unique to examples: ai, jupyter-notebook, llm, python.
- Also covers Data & Retrieval.
- 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 (NVIDIA/cuvs) · observed Sep 20, 2026
- GitHub forks (NVIDIA/cuvs) · observed Sep 20, 2026
- Last push (NVIDIA/cuvs) · observed Sep 20, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: cuvs 854 · examples 3.0k (synced Sep 20, 2026).
Common questions
- What is the difference between cuvs and examples?
- cuvs: A library for vector search and clustering on the GPU. 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 cuvs over examples?
- Choose cuvs over examples when cuvs is primarily Cuda; examples is Jupyter Notebook; License: cuvs is Apache-2.0, examples is MIT; Tags unique to cuvs: anns, clustering, cuda, gpu; cuvs ships Docker support for self-hosted deployment; - When you need high-performance vector operations leveraging the parallel processing power of GPUs, specifically with CUDA.
- When should I choose examples over cuvs?
- Choose examples over cuvs when examples is primarily Jupyter Notebook; cuvs is Cuda; License: examples is MIT, cuvs is Apache-2.0; Tags unique to examples: ai, jupyter-notebook, llm, python; Also covers Data & Retrieval; When you need specific examples and walkthroughs for working with Pinecone's vector database technology using interactive Jupyter Notebooks.
- When should I avoid cuvs?
- - For environments where GPU resources are limited or unavailable because cuVS heavily relies on CUDA's capabilities for performance gains. - When you prioritize portability across different hardware, as cuVS being tied to CUDA means it may not be optimal on non-NVIDIA GPUs or CPU-only systems.
- 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 cuvs or examples more popular on GitHub?
- examples has more GitHub stars (3,043 vs 854). Stars measure visibility, not whether either tool fits your constraints.
- Are cuvs and examples open source?
- Yes - both are open-source projects on GitHub (cuvs: Apache-2.0, examples: MIT).
- Where can I find alternatives to cuvs or examples?
- GraphCanon lists graph-backed alternatives at cuvs alternatives and examples alternatives (cuvs 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, cuvs or examples?
- cuvs: Very active. 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 cuvs and examples?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: cuvs trust report; examples trust report.