--- title: "graphrag-rs vs PixelRAG" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automataia-graphrag-rs-vs-startrail-org-pixelrag" tools: ["automataia-graphrag-rs", "startrail-org-pixelrag"] --- # graphrag-rs vs PixelRAG *GraphCanon updated Sep 20, 2026* ## Verdict Pick graphrag-rs if graphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust; pick PixelRAG if pixelRAG is a Python-based tool that specializes in transforming PDFs into searchable image tiles, enabling efficient and scalable multimodal data retrieval. [graphrag-rs](https://automataia.github.io/graphrag-rs/) reports 527 GitHub stars, 50 forks, and 0 open issues, last pushed Jun 2, 2026. [PixelRAG](https://arxiv.org/pdf/2606.28344) has 9.6k stars, 817 forks, and 24 open issues, last pushed Jul 31, 2026. Figures are from public GitHub metadata via [graphrag-rs's repository](https://github.com/automataIA/graphrag-rs) and [PixelRAG's repository](https://github.com/StarTrail-org/PixelRAG). | | [graphrag-rs](/tools/automataia-graphrag-rs.md) | [PixelRAG](/tools/startrail-org-pixelrag.md) | | --- | --- | --- | | Tagline | GraphRAG-rs implements Graph-based Retrieval Augmented Generation for knowledge graph creation and natural language querying with entity extraction and LLM integration. | Scalable pixel-native search for multimodal data | | Stars | 527 | 9,586 | | Forks | 50 | 817 | | Open issues | 0 | 24 | | Language | Rust | Python | | Adopt for | GraphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust. | PixelRAG is a Python-based tool that specializes in transforming PDFs into searchable image tiles, enabling efficient and scalable multimodal data retrieval. | | Persona | - | - | | Runtime | - | - | | License | MIT | PixelRAG operates under an Apache 2.0 license, which allows for both commercial use and modification of the code. | | Categories | Data & Retrieval, LLM Frameworks | Computer Vision, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphrag-rs](/tools/automataia-graphrag-rs.md) | [PixelRAG](/tools/startrail-org-pixelrag.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 109d | 18d | | Open issues (now) | 0 | 24 | | Stars delta | +5 (30d) | +2.8k (30d) | | Open issues delta | 0 (30d) | +13 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/automataia-graphrag-rs/trust.md) | [trust report](/tools/startrail-org-pixelrag/trust.md) | ## Decision facts: graphrag-rs - **Adopt for:** GraphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust. ## Decision facts: PixelRAG - **Pricing:** unknown - The pricing information is not available from the current repository data. - **Requirements:** Requires installation of 'poppler' to handle PDF files effectively. Use `pip install 'pixelrag[pdf]'` for complete setup. - **Adopt for:** PixelRAG is a Python-based tool that specializes in transforming PDFs into searchable image tiles, enabling efficient and scalable multimodal data retrieval. - **License detail:** PixelRAG operates under an Apache 2.0 license, which allows for both commercial use and modification of the code. ## Choose when ### Choose graphrag-rs if… - graphrag-rs is primarily Rust; PixelRAG is Python. - License: graphrag-rs is MIT, PixelRAG is Apache-2.0. - Tags unique to graphrag-rs: ai, embeddings, entity-extraction, graphrag. - Also covers LLM Frameworks. - Need Rust-based implementation for integration into existing Rust projects ### Choose PixelRAG if… - PixelRAG is primarily Python; graphrag-rs is Rust. - License: PixelRAG is Apache-2.0, graphrag-rs is MIT. - Pricing: The pricing information is not available from the current repository data.. - Requirements: Requires installation of 'poppler' to handle PDF files effectively. Use `pip install 'pixelrag[pdf]'` for complete setup.. - Tags unique to PixelRAG: multimodal, searchengine, vision, vlm. - Also covers Computer Vision. - When your application requires scalable pixel-native search capabilities for multimodal data, particularly from PDF documents ## When NOT to use graphrag-rs - Seeking solutions that offer cloud-hosted machine learning services directly - Projects that demand Python libraries due to ecosystem dependencies ## When NOT to use PixelRAG - For tasks that do not require the conversion of textual or graphically rich content into searchable formats, as PixelRAG is PDF-centric and might not offer value in other data contexts - If you are dealing exclusively with text-based search and your data format doesn't include substantial graphical elements; another tool might be more efficient ## Common questions ### What is the difference between graphrag-rs and PixelRAG? graphrag-rs: GraphRAG-rs implements Graph-based Retrieval Augmented Generation for knowledge graph creation and natural language querying with entity extraction and LLM integration.. PixelRAG: Scalable pixel-native search for multimodal data. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphrag-rs over PixelRAG? Choose graphrag-rs over PixelRAG when graphrag-rs is primarily Rust; PixelRAG is Python; License: graphrag-rs is MIT, PixelRAG is Apache-2.0; Tags unique to graphrag-rs: ai, embeddings, entity-extraction, graphrag; Also covers LLM Frameworks; Need Rust-based implementation for integration into existing Rust projects. ### When should I choose PixelRAG over graphrag-rs? Choose PixelRAG over graphrag-rs when PixelRAG is primarily Python; graphrag-rs is Rust; License: PixelRAG is Apache-2.0, graphrag-rs is MIT; Pricing: The pricing information is not available from the current repository data.; Requirements: Requires installation of 'poppler' to handle PDF files effectively. Use `pip install 'pixelrag[pdf]'` for complete setup.; Tags unique to PixelRAG: multimodal, searchengine, vision, vlm; Also covers Computer Vision; When your application requires scalable pixel-native search capabilities for multimodal data, particularly from PDF documents. ### When should I avoid graphrag-rs? Seeking solutions that offer cloud-hosted machine learning services directly Projects that demand Python libraries due to ecosystem dependencies ### When should I avoid PixelRAG? For tasks that do not require the conversion of textual or graphically rich content into searchable formats, as PixelRAG is PDF-centric and might not offer value in other data contexts If you are dealing exclusively with text-based search and your data format doesn't include substantial graphical elements; another tool might be more efficient ### Is graphrag-rs or PixelRAG more popular on GitHub? PixelRAG has more GitHub stars (9,586 vs 527). Stars measure visibility, not whether either tool fits your constraints. ### Are graphrag-rs and PixelRAG open source? Yes - both are open-source projects on GitHub (graphrag-rs: MIT, PixelRAG: Apache-2.0). ### Where can I find alternatives to graphrag-rs or PixelRAG? GraphCanon lists graph-backed alternatives at [graphrag-rs alternatives](/tools/automataia-graphrag-rs/alternatives) and [PixelRAG alternatives](/tools/startrail-org-pixelrag/alternatives) ([graphrag-rs markdown twin](/tools/automataia-graphrag-rs/alternatives.md), [PixelRAG markdown twin](/tools/startrail-org-pixelrag/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/automataia-graphrag-rs-vs-startrail-org-pixelrag.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphrag-rs or PixelRAG? graphrag-rs: Slowing. PixelRAG: 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 graphrag-rs and PixelRAG? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphrag-rs trust report](/tools/automataia-graphrag-rs/trust); [PixelRAG trust report](/tools/startrail-org-pixelrag/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automataia-graphrag-rs`](/api/graphcanon/graph?tool=automataia-graphrag-rs) - 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/_