--- title: "graphify vs PageIndex" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/graphify-labs-graphify-vs-vectifyai-pageindex" tools: ["graphify-labs-graphify", "vectifyai-pageindex"] --- # graphify vs PageIndex *GraphCanon updated Aug 18, 2026* ## Verdict Pick graphify if graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types; pick PageIndex if pageIndex is a Python-based document indexing system that doesn't rely on vector databases. It's designed for agentic AI tasks where reasoning and context are key. [graphify](https://www.graphify.com) reports 108k GitHub stars, 10k forks, and 978 open issues, last pushed Aug 17, 2026. [PageIndex](https://pageindex.ai) has 35k stars, 3.1k forks, and 157 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [graphify's repository](https://github.com/Graphify-Labs/graphify) and [PageIndex's repository](https://github.com/VectifyAI/PageIndex). | | [graphify](/tools/graphify-labs-graphify.md) | [PageIndex](/tools/vectifyai-pageindex.md) | | --- | --- | --- | | Tagline | Turn any code or documentation into a queryable knowledge graph | Document Index for Vectorless, Reasoning-based RAG | | Stars | 107,507 | 35,204 | | Forks | 10,441 | 3,097 | | Open issues | 978 | 157 | | Language | Python | Python | | Adopt for | Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. | PageIndex is a Python-based document indexing system that doesn't rely on vector databases. It's designed for agentic AI tasks where reasoning and context are key. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphify](/tools/graphify-labs-graphify.md) | [PageIndex](/tools/vectifyai-pageindex.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 978 | 157 | | Stars delta | +17k (30d) | +1.1k (30d) | | Open issues delta | +441 (30d) | +18 (30d) | | Full report | [trust report](/tools/graphify-labs-graphify/trust.md) | [trust report](/tools/vectifyai-pageindex/trust.md) | ## Decision facts: graphify - **Requirements:** Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed. - **Adopt for:** Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. ## Decision facts: PageIndex - **Adopt for:** PageIndex is a Python-based document indexing system that doesn't rely on vector databases. It's designed for agentic AI tasks where reasoning and context are key. ## Choose when ### Choose graphify if… - Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.. - Tags unique to graphify: claude-code, codex, gemini, knowledge-graph. - graphify ships Docker support for self-hosted deployment. - When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ### Choose PageIndex if… - Tags unique to PageIndex: agentic-ai, agents, context-engineering, information-retrieval. - When your agentic AI project requires a non-vector database solution for reasoning and retrieval-augmented generation. - Leaner open-issue backlog (157). ## When NOT to use graphify - If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). - Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ## When NOT to use PageIndex - For projects that strictly require the efficiency of vector databases, as PageIndex operates independently of these technologies. - When your application demands real-time indexing or quick data access methods that are more suited to vector database capabilities. ## Common questions ### What is the difference between graphify and PageIndex? graphify: Turn any code or documentation into a queryable knowledge graph. PageIndex: Document Index for Vectorless, Reasoning-based RAG. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphify over PageIndex? Choose graphify over PageIndex when Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.; Tags unique to graphify: claude-code, codex, gemini, knowledge-graph; graphify ships Docker support for self-hosted deployment; When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ### When should I choose PageIndex over graphify? Choose PageIndex over graphify when Tags unique to PageIndex: agentic-ai, agents, context-engineering, information-retrieval; When your agentic AI project requires a non-vector database solution for reasoning and retrieval-augmented generation; Leaner open-issue backlog (157). ### When should I avoid graphify? If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ### When should I avoid PageIndex? For projects that strictly require the efficiency of vector databases, as PageIndex operates independently of these technologies. When your application demands real-time indexing or quick data access methods that are more suited to vector database capabilities. ### Is graphify or PageIndex more popular on GitHub? graphify has more GitHub stars (107,507 vs 35,204). Stars measure visibility, not whether either tool fits your constraints. ### Are graphify and PageIndex open source? Yes - both are open-source projects on GitHub (graphify: MIT, PageIndex: MIT). ### Where can I find alternatives to graphify or PageIndex? GraphCanon lists graph-backed alternatives at [graphify alternatives](/tools/graphify-labs-graphify/alternatives) and [PageIndex alternatives](/tools/vectifyai-pageindex/alternatives) ([graphify markdown twin](/tools/graphify-labs-graphify/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/graphify-labs-graphify-vs-vectifyai-pageindex.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphify or PageIndex? graphify: Very 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 graphify and PageIndex? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphify trust report](/tools/graphify-labs-graphify/trust); [PageIndex trust report](/tools/vectifyai-pageindex/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=graphify-labs-graphify`](/api/graphcanon/graph?tool=graphify-labs-graphify) - 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/_