--- title: "graphify vs omnigraph" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/graphify-labs-graphify-vs-modernrelay-omnigraph" tools: ["graphify-labs-graphify", "modernrelay-omnigraph"] --- # graphify vs omnigraph *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 omnigraph if omnigraph is a Rust-based Lakehouse-native graph engine that integrates Git-style workflows for managing knowledge graphs leveraging modern data technologies such as Apache Arrow and DataFusion. [graphify](https://www.graphify.com) reports 108k GitHub stars, 10k forks, and 978 open issues, last pushed Aug 17, 2026. [omnigraph](https://omnigraph.dev) has 1.0k stars, 190 forks, and 17 open issues, last pushed Aug 2, 2026. Figures are from public GitHub metadata via [graphify's repository](https://github.com/Graphify-Labs/graphify) and [omnigraph's repository](https://github.com/ModernRelay/omnigraph). | | [graphify](/tools/graphify-labs-graphify.md) | [omnigraph](/tools/modernrelay-omnigraph.md) | | --- | --- | --- | | Tagline | Turn any code or documentation into a queryable knowledge graph | Lakehouse native graph engine with git-style workflows | | Stars | 107,507 | 1,040 | | Forks | 10,441 | 190 | | Open issues | 978 | 17 | | Language | Python | Rust | | Adopt for | Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. | Omnigraph is a Rust-based Lakehouse-native graph engine that integrates Git-style workflows for managing knowledge graphs leveraging modern data technologies such as Apache Arrow and DataFusion. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphify](/tools/graphify-labs-graphify.md) | [omnigraph](/tools/modernrelay-omnigraph.md) | | --- | --- | --- | | Open issues (now) | 978 | 17 | | Stars delta | +17k (30d) | Unknown | | Open issues delta | +441 (30d) | Unknown | | Full report | [trust report](/tools/graphify-labs-graphify/trust.md) | [trust report](/tools/modernrelay-omnigraph/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: omnigraph - **Adopt for:** Omnigraph is a Rust-based Lakehouse-native graph engine that integrates Git-style workflows for managing knowledge graphs leveraging modern data technologies such as Apache Arrow and DataFusion. ## Choose when ### Choose graphify if… - graphify is primarily Python; omnigraph is Rust. - 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, rag. - Also covers AI Agents. - 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 omnigraph if… - omnigraph is primarily Rust; graphify is Python. - Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database. - Use Omnigraph if your project involves complex knowledge graph management within a lakehouse architecture, as it offers native integration to facilitate efficient handling of large datasets. ## 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 omnigraph - Avoid Omnigraph if you prefer or need a Java-based solution, as it might not align with the runtime requirements of your existing technology stack. - Omnigraph may not be suitable for simple or small-scale graph projects that do not require advanced versioning and collaboration features akin to Git workflows. ## Common questions ### What is the difference between graphify and omnigraph? graphify: Turn any code or documentation into a queryable knowledge graph. omnigraph: Lakehouse native graph engine with git-style workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphify over omnigraph? Choose graphify over omnigraph when graphify is primarily Python; omnigraph is Rust; 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, rag; Also covers AI Agents; 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 omnigraph over graphify? Choose omnigraph over graphify when omnigraph is primarily Rust; graphify is Python; Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database; Use Omnigraph if your project involves complex knowledge graph management within a lakehouse architecture, as it offers native integration to facilitate efficient handling of large datasets. ### 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 omnigraph? Avoid Omnigraph if you prefer or need a Java-based solution, as it might not align with the runtime requirements of your existing technology stack. Omnigraph may not be suitable for simple or small-scale graph projects that do not require advanced versioning and collaboration features akin to Git workflows. ### Is graphify or omnigraph more popular on GitHub? graphify has more GitHub stars (107,507 vs 1,040). Stars measure visibility, not whether either tool fits your constraints. ### Are graphify and omnigraph open source? Yes - both are open-source projects on GitHub (graphify: MIT, omnigraph: MIT). ### Where can I find alternatives to graphify or omnigraph? GraphCanon lists graph-backed alternatives at [graphify alternatives](/tools/graphify-labs-graphify/alternatives) and [omnigraph alternatives](/tools/modernrelay-omnigraph/alternatives) ([graphify markdown twin](/tools/graphify-labs-graphify/alternatives.md), [omnigraph markdown twin](/tools/modernrelay-omnigraph/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-modernrelay-omnigraph.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphify or omnigraph? graphify: Very active. omnigraph: 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 omnigraph? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphify trust report](/tools/graphify-labs-graphify/trust); [omnigraph trust report](/tools/modernrelay-omnigraph/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/_