Comparison
vectordb vs cuvs
Verdict
Pick vectordb if vectordb is a Python library for efficient vector database operations, supporting local and cloud-based deployment, and integration with various communication protocols; pick cuvs if cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering.
Markdown twin · vectordb alternatives · cuvs alternatives
GraphCanon updated Sep 20, 2026
Trust & integrity
| Signal | vectordb | cuvs |
|---|---|---|
| Maintenance | Dormant (927d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-09-18 As of Sep 18, 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
- vectordb
- A Python vector database for embedding similarity and neural search.
- cuvs
- A library for vector search and clustering on the GPU
Stars
- vectordb
- 653
- cuvs
- 854
Forks
- vectordb
- 50
- cuvs
- 236
Open issues
- vectordb
- 9
- cuvs
- 738
Language
- vectordb
- Python
- cuvs
- Cuda
Adopt for
- vectordb
- vectordb is a Python library for efficient vector database operations, supporting local and cloud-based deployment, and integration with various communication protocols.
- cuvs
- cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering.
Persona
- vectordb
- -
- cuvs
- -
Runtime
- vectordb
- -
- cuvs
- -
License
- vectordb
- Apache-2.0
- cuvs
- Apache-2.0
Last pushed
- vectordb
- Mar 4, 2024
- cuvs
- Sep 20, 2026
Categories
- vectordb
- Vector Databases
- cuvs
- Vector Databases
Trust and health
Maintenance
- vectordb
- Dormant (18%)
- cuvs
- Very active (96%)
Days since push
- vectordb
- 927d
- cuvs
- 0d
Open issues (now)
- vectordb
- 9
- cuvs
- 738
Stars delta
- vectordb
- +3 (30d)
- cuvs
- +33 (30d)
Open issues delta
- vectordb
- 0 (30d)
- cuvs
- +93 (30d)
OSV dependency advisories
- vectordb
- No published findings from this source as of 2026-09-18
- cuvs
- No lockfile (source not queried)
Full report
- vectordb
- Trust report
- cuvs
- Trust report
Choose vectordb if…
- vectordb is primarily Python; cuvs is Cuda.
- Tags unique to vectordb: embedding-similarity, neural-search, sentence-embeddings, vector-database.
- Use vectordb when you need a Python library that supports both local and cloud-based deployment for vector database operations.
When NOT to use vectordb
- Avoid vectordb if you are looking for a solution that does not support Python or if you prefer a non-Python environment.
- Do not use vectordb if you need a vector database that does not offer cloud-based deployment options or if you strictly require on-premises solutions.
- If your project does not require or benefit from integration with gRPC, HTTP, or Websocket, vectordb might not be the best choice.
Choose cuvs if…
- cuvs is primarily Cuda; vectordb is Python.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (jina-ai/vectordb) · observed Sep 20, 2026
- GitHub forks (jina-ai/vectordb) · observed Sep 20, 2026
- Last push (jina-ai/vectordb) · observed Mar 4, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- 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 on cards: vectordb 653 · cuvs 854 (synced Sep 20, 2026).
Common questions
- What is the difference between vectordb and cuvs?
- vectordb: A Python vector database for embedding similarity and neural search.. cuvs: A library for vector search and clustering on the GPU. See the comparison table for live GitHub stats and shared categories.
- When should I choose vectordb over cuvs?
- Choose vectordb over cuvs when vectordb is primarily Python; cuvs is Cuda; Tags unique to vectordb: embedding-similarity, neural-search, sentence-embeddings, vector-database; Use vectordb when you need a Python library that supports both local and cloud-based deployment for vector database operations.
- When should I choose cuvs over vectordb?
- Choose cuvs over vectordb when cuvs is primarily Cuda; vectordb is Python; 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 avoid vectordb?
- Avoid vectordb if you are looking for a solution that does not support Python or if you prefer a non-Python environment. Do not use vectordb if you need a vector database that does not offer cloud-based deployment options or if you strictly require on-premises solutions. If your project does not require or benefit from integration with gRPC, HTTP, or Websocket, vectordb might not be the best choice.
- 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.
- Is vectordb or cuvs more popular on GitHub?
- cuvs has more GitHub stars (854 vs 653). Stars measure visibility, not whether either tool fits your constraints.
- Are vectordb and cuvs open source?
- Yes - both are open-source projects on GitHub (vectordb: Apache-2.0, cuvs: Apache-2.0).
- Where can I find alternatives to vectordb or cuvs?
- GraphCanon lists graph-backed alternatives at vectordb alternatives and cuvs alternatives (vectordb markdown twin, cuvs 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, vectordb or cuvs?
- vectordb: Dormant. cuvs: 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 vectordb and cuvs?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: vectordb trust report; cuvs trust report.