Comparison
rag_api vs VectorDBBench
Verdict
Pick rag_api if key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration; pick VectorDBBench if vectorDBBench is a benchmark tool for evaluating vector databases written in Python under the MIT license.
Markdown twin · rag_api alternatives · VectorDBBench alternatives
GraphCanon updated Sep 20, 2026
9views this month
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Trust & integrity
| Signal | rag_api | VectorDBBench |
|---|---|---|
| Maintenance | Steady (35d since push) As of Sep 20, 2026 · github_public_v1 | Active (8d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal 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
- rag_api
- ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
- VectorDBBench
- Benchmark for vector databases
Stars
- rag_api
- 901
- VectorDBBench
- 1.2k
Forks
- rag_api
- 404
- VectorDBBench
- 439
Open issues
- rag_api
- 45
- VectorDBBench
- 184
Language
- rag_api
- Python
- VectorDBBench
- Python
Adopt for
- rag_api
- Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration
- VectorDBBench
- VectorDBBench is a benchmark tool for evaluating vector databases written in Python under the MIT license.
Persona
- rag_api
- -
- VectorDBBench
- -
Runtime
- rag_api
- -
- VectorDBBench
- -
License
- rag_api
- MIT
- VectorDBBench
- MIT
Last pushed
- rag_api
- Aug 15, 2026
- VectorDBBench
- Sep 11, 2026
Categories
- rag_api
- Data & Retrieval, Vector Databases
- VectorDBBench
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- rag_api
- Steady (60%)
- VectorDBBench
- Active (82%)
Days since push
- rag_api
- 35d
- VectorDBBench
- 8d
Open issues (now)
- rag_api
- 45
- VectorDBBench
- 184
Stars delta
- rag_api
- +35 (30d)
- VectorDBBench
- +31 (30d)
Open issues delta
- rag_api
- -2 (30d)
- VectorDBBench
- +30 (30d)
Owner type
- rag_api
- User
- VectorDBBench
- Organization
Full report
- rag_api
- Trust report
- VectorDBBench
- Trust report
Shared compatibility
- Python · rag_api: Python runtime · VectorDBBench: Python runtime
Choose rag_api if…
- Tags unique to rag_api: api, api-rest, embeddings, fastapi.
- When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
- Leaner open-issue backlog (45).
When NOT to use rag_api
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints.
- Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
Choose VectorDBBench if…
- Tags unique to VectorDBBench: benchmark, cost-effectiveness, performance, vector-database.
- When you need a comprehensive performance analysis of vector database solutions using Python
- More GitHub stars (1.2k vs 901) - visibility, not fit.
When NOT to use VectorDBBench
- If your evaluation framework requires languages other than Python or licenses other than MIT
- When benchmarking non-vector type databases, as VectorDBBench is specialized for vector databases
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (danny-avila/rag_api) · observed Sep 20, 2026
- GitHub forks (danny-avila/rag_api) · observed Sep 20, 2026
- Last push (danny-avila/rag_api) · observed Aug 15, 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 (zilliztech/VectorDBBench) · observed Sep 20, 2026
- GitHub forks (zilliztech/VectorDBBench) · observed Sep 20, 2026
- Last push (zilliztech/VectorDBBench) · observed Sep 11, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: rag_api 901 · VectorDBBench 1.2k (synced Sep 20, 2026).
Common questions
- What is the difference between rag_api and VectorDBBench?
- rag_api: ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector. VectorDBBench: Benchmark for vector databases. See the comparison table for live GitHub stats and shared categories.
- When should I choose rag_api over VectorDBBench?
- Choose rag_api over VectorDBBench when Tags unique to rag_api: api, api-rest, embeddings, fastapi; When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage; Leaner open-issue backlog (45).
- When should I choose VectorDBBench over rag_api?
- Choose VectorDBBench over rag_api when Tags unique to VectorDBBench: benchmark, cost-effectiveness, performance, vector-database; When you need a comprehensive performance analysis of vector database solutions using Python; More GitHub stars (1.2k vs 901) - visibility, not fit.
- When should I avoid rag_api?
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints. Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
- When should I avoid VectorDBBench?
- If your evaluation framework requires languages other than Python or licenses other than MIT When benchmarking non-vector type databases, as VectorDBBench is specialized for vector databases
- Is rag_api or VectorDBBench more popular on GitHub?
- VectorDBBench has more GitHub stars (1,178 vs 901). Stars measure visibility, not whether either tool fits your constraints.
- Are rag_api and VectorDBBench open source?
- Yes - both are open-source projects on GitHub (rag_api: MIT, VectorDBBench: MIT).
- Where can I find alternatives to rag_api or VectorDBBench?
- GraphCanon lists graph-backed alternatives at rag_api alternatives and VectorDBBench alternatives (rag_api markdown twin, VectorDBBench 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, rag_api or VectorDBBench?
- rag_api: Steady. VectorDBBench: 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 rag_api and VectorDBBench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rag_api trust report; VectorDBBench trust report.