--- title: "EnterpriseRAG-Bench vs PageIndex" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/onyx-dot-app-enterpriserag-bench-vs-vectifyai-pageindex" tools: ["onyx-dot-app-enterpriserag-bench", "vectifyai-pageindex"] --- # EnterpriseRAG-Bench vs PageIndex *GraphCanon updated Sep 20, 2026* ## 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. [EnterpriseRAG-Bench](https://www.onyx.app/) reports 562 GitHub stars, 62 forks, and 13 open issues, last pushed Sep 3, 2026. [PageIndex](https://pageindex.ai) has 36k stars, 3.1k forks, and 105 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [EnterpriseRAG-Bench's repository](https://github.com/onyx-dot-app/EnterpriseRAG-Bench) and [PageIndex's repository](https://github.com/VectifyAI/PageIndex). | | [EnterpriseRAG-Bench](/tools/onyx-dot-app-enterpriserag-bench.md) | [PageIndex](/tools/vectifyai-pageindex.md) | | --- | --- | --- | | Tagline | Dataset and benchmark for RAG on company internal documents | Document Index for Vectorless, Reasoning-based RAG | | Stars | 562 | 35,705 | | Forks | 62 | 3,148 | | Open issues | 13 | 105 | | Language | - | Python | | Adopt for | EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data. | 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 | - | - | | Runtime | - | - | | License | MIT license allows free usage and modification with attribution. | MIT | | Categories | Data & Retrieval, Evaluation & Observability | Data & Retrieval, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [EnterpriseRAG-Bench](/tools/onyx-dot-app-enterpriserag-bench.md) | [PageIndex](/tools/vectifyai-pageindex.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 16d | 0d | | Open issues (now) | 13 | 105 | | Stars delta | +73 (30d) | +501 (30d) | | Open issues delta | +4 (30d) | -52 (30d) | | Full report | [trust report](/tools/onyx-dot-app-enterpriserag-bench/trust.md) | [trust report](/tools/vectifyai-pageindex/trust.md) | ## Decision facts: EnterpriseRAG-Bench - **Adopt for:** EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data. - **License detail:** MIT license allows free usage and modification with attribution. ## Decision facts: PageIndex - **Adopt for:** PageIndex is a Python-based tool for indexing documents for retrieval-augmented generation tasks, emphasizing reasoning-based retrieval without heavy reliance on vector databases. ## Choose when ### 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). ### 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 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 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. ## 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](/tools/onyx-dot-app-enterpriserag-bench/alternatives) and [PageIndex alternatives](/tools/vectifyai-pageindex/alternatives) ([EnterpriseRAG-Bench markdown twin](/tools/onyx-dot-app-enterpriserag-bench/alternatives.md), [PageIndex markdown twin](/tools/vectifyai-pageindex/alternatives.md)), 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](/compare/onyx-dot-app-enterpriserag-bench-vs-vectifyai-pageindex.md) 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](/tools/onyx-dot-app-enterpriserag-bench/trust); [PageIndex trust report](/tools/vectifyai-pageindex/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=onyx-dot-app-enterpriserag-bench`](/api/graphcanon/graph?tool=onyx-dot-app-enterpriserag-bench) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_