Home/Compare/EnterpriseRAG-Bench vs PageIndex

Comparison

EnterpriseRAG-Bench vs PageIndex

Verdict

Pick EnterpriseRAG-Bench if enterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data; pick PageIndex if pageIndex is a Python-based tool for indexing documents for retrieval-augmented generation tasks, emphasizing reasoning-based retrieval without heavy reliance on vector databases.

Markdown twin · EnterpriseRAG-Bench alternatives · PageIndex alternatives

GraphCanon updated Sep 20, 2026

EnterpriseRAG-Bench logo

EnterpriseRAG-Bench

onyx-dot-app/EnterpriseRAG-Bench

★ 562pushed Sep 3, 2026
vs
PageIndex logo

PageIndex

VectifyAI/PageIndex

★ 36kpushed Sep 18, 2026

Trust & integrity

SignalEnterpriseRAG-BenchPageIndex
Maintenance
Active (16d since push)
As of Sep 20, 2026 · github_public_v1
Very active (0d since push)
As of Sep 18, 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 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
As of Sep 18, 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

EnterpriseRAG-Bench
Dataset and benchmark for RAG on company internal documents
PageIndex
Document Index for Vectorless, Reasoning-based RAG

Stars

EnterpriseRAG-Bench
562
PageIndex
36k

Forks

EnterpriseRAG-Bench
62
PageIndex
3.1k

Open issues

EnterpriseRAG-Bench
13
PageIndex
105

Language

EnterpriseRAG-Bench
-
PageIndex
Python

Adopt for

EnterpriseRAG-Bench
EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data.
PageIndex
PageIndex is a Python-based tool for indexing documents for retrieval-augmented generation tasks, emphasizing reasoning-based retrieval without heavy reliance on vector databases.

Persona

EnterpriseRAG-Bench
-
PageIndex
-

Runtime

EnterpriseRAG-Bench
-
PageIndex
-

License

EnterpriseRAG-Bench
MIT license allows free usage and modification with attribution.
PageIndex
MIT

Last pushed

EnterpriseRAG-Bench
Sep 3, 2026
PageIndex
Sep 18, 2026

Categories

EnterpriseRAG-Bench
Data & Retrieval, Evaluation & Observability
PageIndex
Data & Retrieval, Evaluation & Observability

Trust and health

Maintenance

EnterpriseRAG-Bench
Active (82%)
PageIndex
Very active (96%)

Days since push

EnterpriseRAG-Bench
16d
PageIndex
0d

Open issues (now)

EnterpriseRAG-Bench
13
PageIndex
105

Stars delta

EnterpriseRAG-Bench
+73 (30d)
PageIndex
+501 (30d)

Open issues delta

EnterpriseRAG-Bench
+4 (30d)
PageIndex
-52 (30d)

OSV dependency advisories

EnterpriseRAG-Bench
No lockfile (source not queried)
PageIndex
Published findings

Full report

EnterpriseRAG-Bench
Trust report
PageIndex
Trust report

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
  • Leaner open-issue backlog (13).

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

Choose PageIndex if…

  • Tags unique to PageIndex: agentic-ai, agents, ai-agents, context-engineering.
  • Use PageIndex when you need to index documents for retrieval-augmented generation tasks that require reasoning-based retrieval.
  • More GitHub stars (36k vs 562) - visibility, not fit.

When NOT to use PageIndex

  • Do not use PageIndex if your application heavily relies on vector databases for document retrieval, as PageIndex is designed to work without them.
  • Avoid PageIndex if you need to handle documents larger than the context window of the model you are using, as PageIndex may not be able to process them.
  • Do not use PageIndex if you require a tool that can handle documents that do not fit into the context window at all, as PageIndex may not be suitable for such cases.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: EnterpriseRAG-Bench 562 · PageIndex 36k (synced Sep 20, 2026).

Common questions

What is the difference between EnterpriseRAG-Bench and PageIndex?
EnterpriseRAG-Bench: Dataset and benchmark for RAG on company internal documents. PageIndex: Document Index for Vectorless, Reasoning-based RAG. See the comparison table for live GitHub stats and shared categories.
When should I choose EnterpriseRAG-Bench over PageIndex?
Choose EnterpriseRAG-Bench over PageIndex 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; Leaner open-issue backlog (13).
When should I choose PageIndex over EnterpriseRAG-Bench?
Choose PageIndex over EnterpriseRAG-Bench when Tags unique to PageIndex: agentic-ai, agents, ai-agents, context-engineering; Use PageIndex when you need to index documents for retrieval-augmented generation tasks that require reasoning-based retrieval; More GitHub stars (36k vs 562) - visibility, not fit.
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
When should I avoid PageIndex?
Do not use PageIndex if your application heavily relies on vector databases for document retrieval, as PageIndex is designed to work without them. Avoid PageIndex if you need to handle documents larger than the context window of the model you are using, as PageIndex may not be able to process them. Do not use PageIndex if you require a tool that can handle documents that do not fit into the context window at all, as PageIndex may not be suitable for such cases.
Is EnterpriseRAG-Bench or PageIndex more popular on GitHub?
PageIndex has more GitHub stars (35,705 vs 562). Stars measure visibility, not whether either tool fits your constraints.
Are EnterpriseRAG-Bench and PageIndex open source?
Yes - both are open-source projects on GitHub (EnterpriseRAG-Bench: MIT, PageIndex: MIT).
Where can I find alternatives to EnterpriseRAG-Bench or PageIndex?
GraphCanon lists graph-backed alternatives at EnterpriseRAG-Bench alternatives and PageIndex alternatives (EnterpriseRAG-Bench markdown twin, PageIndex 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, EnterpriseRAG-Bench or PageIndex?
EnterpriseRAG-Bench: Active. PageIndex: 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 EnterpriseRAG-Bench and PageIndex?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: EnterpriseRAG-Bench trust report; PageIndex trust report.

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