--- title: "feast vs omnigraph" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/feast-dev-feast-vs-modernrelay-omnigraph" tools: ["feast-dev-feast", "modernrelay-omnigraph"] --- # feast vs omnigraph *GraphCanon updated Aug 3, 2026* ## Verdict Pick feast if feast, an open-source feature store for AI/ML, facilitates efficient management and retrieval of features used in machine learning models; 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. [feast](https://feast.dev) reports 7.2k GitHub stars, 1.4k forks, and 390 open issues, last pushed Jul 31, 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 [feast's repository](https://github.com/feast-dev/feast) and [omnigraph's repository](https://github.com/ModernRelay/omnigraph). | | [feast](/tools/feast-dev-feast.md) | [omnigraph](/tools/modernrelay-omnigraph.md) | | --- | --- | --- | | Tagline | The Open Source Feature Store for AI/ML | Lakehouse native graph engine with git-style workflows | | Stars | 7,188 | 1,040 | | Forks | 1,392 | 190 | | Open issues | 390 | 17 | | Language | Python | Rust | | Adopt for | Feast, an open-source feature store for AI/ML, facilitates efficient management and retrieval of features used in machine learning models. | 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 | Apache-2.0 | MIT | | Categories | Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [feast](/tools/feast-dev-feast.md) | [omnigraph](/tools/modernrelay-omnigraph.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 390 | 17 | | Full report | [trust report](/tools/feast-dev-feast/trust.md) | [trust report](/tools/modernrelay-omnigraph/trust.md) | ## Decision facts: feast - **Adopt for:** Feast, an open-source feature store for AI/ML, facilitates efficient management and retrieval of features used in machine learning models. ## 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 feast if… - feast is primarily Python; omnigraph is Rust. - License: feast is Apache-2.0, omnigraph is MIT. - Tags unique to feast: big-data, data-engineering, data-quality, data-science. - Use Feast when your project requires versioning of features to support experimentation and model evolution over time, as it allows you to seamlessly retrieve historical feature data. ### Choose omnigraph if… - omnigraph is primarily Rust; feast is Python. - License: omnigraph is MIT, feast is Apache-2.0. - Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database. - omnigraph ships Docker support for self-hosted deployment. - 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 feast - Avoid Feast in scenarios where your project needs are minimal, such as smaller datasets or simpler projects that do not require the overhead of feature versioning or management. - Do not use Feast if you prefer a more generalized data storage solution without specific features geared towards ML feature management. Competitors might be better for broader data manipulation tasks. ## 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 feast and omnigraph? feast: The Open Source Feature Store for AI/ML. omnigraph: Lakehouse native graph engine with git-style workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose feast over omnigraph? Choose feast over omnigraph when feast is primarily Python; omnigraph is Rust; License: feast is Apache-2.0, omnigraph is MIT; Tags unique to feast: big-data, data-engineering, data-quality, data-science; Use Feast when your project requires versioning of features to support experimentation and model evolution over time, as it allows you to seamlessly retrieve historical feature data. ### When should I choose omnigraph over feast? Choose omnigraph over feast when omnigraph is primarily Rust; feast is Python; License: omnigraph is MIT, feast is Apache-2.0; Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database; omnigraph ships Docker support for self-hosted deployment; 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 feast? Avoid Feast in scenarios where your project needs are minimal, such as smaller datasets or simpler projects that do not require the overhead of feature versioning or management. Do not use Feast if you prefer a more generalized data storage solution without specific features geared towards ML feature management. Competitors might be better for broader data manipulation tasks. ### 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 feast or omnigraph more popular on GitHub? feast has more GitHub stars (7,188 vs 1,040). Stars measure visibility, not whether either tool fits your constraints. ### Are feast and omnigraph open source? Yes - both are open-source projects on GitHub (feast: Apache-2.0, omnigraph: MIT). ### Where can I find alternatives to feast or omnigraph? GraphCanon lists graph-backed alternatives at [feast alternatives](/tools/feast-dev-feast/alternatives) and [omnigraph alternatives](/tools/modernrelay-omnigraph/alternatives) ([feast markdown twin](/tools/feast-dev-feast/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/feast-dev-feast-vs-modernrelay-omnigraph.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, feast or omnigraph? feast: 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 feast and omnigraph? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [feast trust report](/tools/feast-dev-feast/trust); [omnigraph trust report](/tools/modernrelay-omnigraph/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=feast-dev-feast`](/api/graphcanon/graph?tool=feast-dev-feast) - 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/_