--- title: "EnterpriseRAG-Bench vs HippoRAG" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/onyx-dot-app-enterpriserag-bench-vs-osu-nlp-group-hipporag" tools: ["onyx-dot-app-enterpriserag-bench", "osu-nlp-group-hipporag"] --- # EnterpriseRAG-Bench vs HippoRAG *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 HippoRAG if hippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. [EnterpriseRAG-Bench](https://www.onyx.app/) reports 562 GitHub stars, 62 forks, and 13 open issues, last pushed Sep 3, 2026. [HippoRAG](https://arxiv.org/abs/2405.14831) has 4.0k stars, 428 forks, and 9 open issues, last pushed Sep 3, 2026. Figures are from public GitHub metadata via [EnterpriseRAG-Bench's repository](https://github.com/onyx-dot-app/EnterpriseRAG-Bench) and [HippoRAG's repository](https://github.com/OSU-NLP-Group/HippoRAG). | | [EnterpriseRAG-Bench](/tools/onyx-dot-app-enterpriserag-bench.md) | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | | --- | --- | --- | | Tagline | Dataset and benchmark for RAG on company internal documents | A RAG framework enabling LLMs to integrate knowledge from external documents | | Stars | 562 | 4,012 | | Forks | 62 | 428 | | Open issues | 13 | 9 | | Language | - | Python | | Adopt for | EnterpriseRAG-Bench specializes in benchmarking RAG models on company internal documents, offering specific evaluation metrics for enterprise-level data. | HippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. | | Persona | - | - | | Runtime | - | - | | License | MIT license allows free usage and modification with attribution. | MIT | | Categories | Data & Retrieval, Evaluation & Observability | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [EnterpriseRAG-Bench](/tools/onyx-dot-app-enterpriserag-bench.md) | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | | --- | --- | --- | | Days since push | 16d | 14d | | Open issues (now) | 13 | 9 | | Stars delta | +73 (30d) | +110 (30d) | | Open issues delta | +4 (30d) | +2 (30d) | | Full report | [trust report](/tools/onyx-dot-app-enterpriserag-bench/trust.md) | [trust report](/tools/osu-nlp-group-hipporag/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: HippoRAG - **Requirements:** Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment. - **Adopt for:** HippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. ## Choose when ### Choose EnterpriseRAG-Bench if… - Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation. - Also covers Evaluation & Observability. - When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation ### Choose HippoRAG if… - Requirements: Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment.. - Tags unique to HippoRAG: external documents, knowledge graphs, knowledge integration, llms. - Also covers LLM Frameworks. - When you need a framework that integrates knowledge from external documents into LLMs in a manner inspired by human long-term memory. ## 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 HippoRAG - If your project does not require the integration of knowledge from external documents into LLMs in a manner inspired by human long-term memory. - When personalized page rank and knowledge graphs are not necessary for your project's knowledge retrieval and integration needs. - If you are not using Python 3.10 or do not wish to manage a project-local environment with Conda or `uv`. ## Common questions ### What is the difference between EnterpriseRAG-Bench and HippoRAG? EnterpriseRAG-Bench: Dataset and benchmark for RAG on company internal documents. HippoRAG: A RAG framework enabling LLMs to integrate knowledge from external documents. See the comparison table for live GitHub stats and shared categories. ### When should I choose EnterpriseRAG-Bench over HippoRAG? Choose EnterpriseRAG-Bench over HippoRAG when Tags unique to EnterpriseRAG-Bench: benchmark, dataset, enterprise-search, evaluation; Also covers Evaluation & Observability; When you need to evaluate retrieval-augmented generation models specifically for processing extensive and complex enterprise documentation. ### When should I choose HippoRAG over EnterpriseRAG-Bench? Choose HippoRAG over EnterpriseRAG-Bench when Requirements: Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment.; Tags unique to HippoRAG: external documents, knowledge graphs, knowledge integration, llms; Also covers LLM Frameworks; When you need a framework that integrates knowledge from external documents into LLMs in a manner inspired by human long-term memory. ### 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 HippoRAG? If your project does not require the integration of knowledge from external documents into LLMs in a manner inspired by human long-term memory. When personalized page rank and knowledge graphs are not necessary for your project's knowledge retrieval and integration needs. If you are not using Python 3.10 or do not wish to manage a project-local environment with Conda or `uv`. ### Is EnterpriseRAG-Bench or HippoRAG more popular on GitHub? HippoRAG has more GitHub stars (4,012 vs 562). Stars measure visibility, not whether either tool fits your constraints. ### Are EnterpriseRAG-Bench and HippoRAG open source? Yes - both are open-source projects on GitHub (EnterpriseRAG-Bench: MIT, HippoRAG: MIT). ### Where can I find alternatives to EnterpriseRAG-Bench or HippoRAG? GraphCanon lists graph-backed alternatives at [EnterpriseRAG-Bench alternatives](/tools/onyx-dot-app-enterpriserag-bench/alternatives) and [HippoRAG alternatives](/tools/osu-nlp-group-hipporag/alternatives) ([EnterpriseRAG-Bench markdown twin](/tools/onyx-dot-app-enterpriserag-bench/alternatives.md), [HippoRAG markdown twin](/tools/osu-nlp-group-hipporag/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-osu-nlp-group-hipporag.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, EnterpriseRAG-Bench or HippoRAG? EnterpriseRAG-Bench: Active. HippoRAG: 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 HippoRAG? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [EnterpriseRAG-Bench trust report](/tools/onyx-dot-app-enterpriserag-bench/trust); [HippoRAG trust report](/tools/osu-nlp-group-hipporag/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/_