Comparison
ragtune vs EnterpriseRAG-Bench
Verdict
Pick ragtune if ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer; pick EnterpriseRAG-Bench if enterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data.
Markdown twin · ragtune alternatives · EnterpriseRAG-Bench alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | ragtune | EnterpriseRAG-Bench |
|---|---|---|
| Maintenance | Slowing (129d since push) As of 3w · github_public_v1 | Steady (81d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings 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
- ragtune
- Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers
- EnterpriseRAG-Bench
- Dataset and benchmark for RAG on company internal documents
Stars
- ragtune
- 13
- EnterpriseRAG-Bench
- 489
Forks
- ragtune
- 1
- EnterpriseRAG-Bench
- 52
Open issues
- ragtune
- 0
- EnterpriseRAG-Bench
- 9
Language
- ragtune
- Go
- EnterpriseRAG-Bench
- -
Adopt for
- ragtune
- Ragtune is a Go-based benchmarking tool for RAG retrieval systems that allows users to inspect, debug, benchmark, and tune the retrieval layer.
- EnterpriseRAG-Bench
- EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data.
Persona
- ragtune
- -
- EnterpriseRAG-Bench
- -
Runtime
- ragtune
- -
- EnterpriseRAG-Bench
- -
License
- ragtune
- MIT
- EnterpriseRAG-Bench
- MIT license allows free usage and modification with attribution.
Last pushed
- ragtune
- Mar 25, 2026
- EnterpriseRAG-Bench
- May 8, 2026
Categories
- ragtune
- Data & Retrieval, Evaluation & Observability
- EnterpriseRAG-Bench
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- ragtune
- Slowing (36%)
- EnterpriseRAG-Bench
- Steady (60%)
Days since push
- ragtune
- 129d
- EnterpriseRAG-Bench
- 81d
Open issues (now)
- ragtune
- 0
- EnterpriseRAG-Bench
- 9
Owner type
- ragtune
- User
- EnterpriseRAG-Bench
- Organization
OSV dependency advisories
- ragtune
- Published findings
- EnterpriseRAG-Bench
- No lockfile (source not queried)
Full report
- ragtune
- Trust report
- EnterpriseRAG-Bench
- Trust report
Choose ragtune if…
- Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation.
- For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly.
- Leaner open-issue backlog (0).
When NOT to use ragtune
- If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort.
- When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.
Choose EnterpriseRAG-Bench if…
- Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation.
- When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation
- More GitHub stars (489 vs 13) - visibility, not fit.
When NOT to use EnterpriseRAG-Bench
- Avoid if your focus is on general web or public-domain document benchmarking, as EnterpriseRAG-Bench is tuned exclusively for company internal documents
- Do not use if you require a solution that supports languages other than those implied by the existing dataset without further customization
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (metawake/ragtune) · observed Aug 2, 2026
- GitHub forks (metawake/ragtune) · observed Aug 2, 2026
- Last push (metawake/ragtune) · observed Mar 25, 2026
- License file (MIT) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (onyx-dot-app/EnterpriseRAG-Bench) · observed Jul 28, 2026
- GitHub forks (onyx-dot-app/EnterpriseRAG-Bench) · observed Jul 28, 2026
- Last push (onyx-dot-app/EnterpriseRAG-Bench) · observed May 8, 2026
- License file (MIT) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ragtune 13 · EnterpriseRAG-Bench 489 (synced Aug 2, 2026).
Common questions
- What is the difference between ragtune and EnterpriseRAG-Bench?
- ragtune: Benchmarking tool for RAG retrieval, aiding in tuning and evaluating retrieval layers. EnterpriseRAG-Bench: Dataset and benchmark for RAG on company internal documents. See the comparison table for live GitHub stats and shared categories.
- When should I choose ragtune over EnterpriseRAG-Bench?
- Choose ragtune over EnterpriseRAG-Bench when Tags unique to ragtune: benchmarking, embeddings, metrics, retrieval-augmented-generation; For organizations using multiple vector search engines like Chroma or Pinecone because Ragtune supports them directly; Leaner open-issue backlog (0).
- When should I choose EnterpriseRAG-Bench over ragtune?
- Choose EnterpriseRAG-Bench over ragtune when Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation; When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation; More GitHub stars (489 vs 13) - visibility, not fit.
- When should I avoid ragtune?
- If your project relies on languages other than Go, as Ragtune might not integrate smoothly without additional effort. When the primary focus of retrieval layer tuning lies outside supported vector search engines like Chroma or Qdrant and no customization can be applied via the tool.
- When should I avoid EnterpriseRAG-Bench?
- Avoid if your focus is on general web or public-domain document benchmarking, as EnterpriseRAG-Bench is tuned exclusively for company internal documents Do not use if you require a solution that supports languages other than those implied by the existing dataset without further customization
- Is ragtune or EnterpriseRAG-Bench more popular on GitHub?
- EnterpriseRAG-Bench has more GitHub stars (489 vs 13). Stars measure visibility, not whether either tool fits your constraints.
- Are ragtune and EnterpriseRAG-Bench open source?
- Yes - both are open-source projects on GitHub (ragtune: MIT, EnterpriseRAG-Bench: MIT).
- Where can I find alternatives to ragtune or EnterpriseRAG-Bench?
- GraphCanon lists graph-backed alternatives at ragtune alternatives and EnterpriseRAG-Bench alternatives (ragtune markdown twin, EnterpriseRAG-Bench 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, ragtune or EnterpriseRAG-Bench?
- ragtune: Slowing. EnterpriseRAG-Bench: Steady. 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 ragtune and EnterpriseRAG-Bench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ragtune trust report; EnterpriseRAG-Bench trust report.