--- title: "omnigraph vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/modernrelay-omnigraph-vs-shubhamsaboo-awesome-llm-apps" tools: ["modernrelay-omnigraph", "shubhamsaboo-awesome-llm-apps"] --- # omnigraph vs awesome-llm-apps *GraphCanon updated Sep 20, 2026* ## Verdict Pick omnigraph if omnigraph is a graph engine designed for lakehouse environments, featuring git-style workflows for managing graph data. It supports operations on knowledge graphs and graph databases, and integrates with technologies, as; pick awesome-llm-apps if awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy. [omnigraph](https://omnigraph.dev) reports 1.1k GitHub stars, 250 forks, and 56 open issues, last pushed Sep 17, 2026. [awesome-llm-apps](https://www.theunwindai.com) has 136k stars, 20k forks, and 10 open issues, last pushed Sep 2, 2026. Figures are from public GitHub metadata via [omnigraph's repository](https://github.com/ModernRelay/omnigraph) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [omnigraph](/tools/modernrelay-omnigraph.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | Lakehouse native graph engine with git-style workflows | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 1,136 | 136,444 | | Forks | 250 | 20,078 | | Open issues | 56 | 10 | | Language | Rust | Python | | Adopt for | Omnigraph is a graph engine designed for lakehouse environments, featuring git-style workflows for managing graph data. It supports operations on knowledge graphs and graph databases, and integrates with technologies, as | awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. | | Persona | - | - | | Runtime | - | - | | License | MIT | The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. | | Categories | Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [omnigraph](/tools/modernrelay-omnigraph.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Days since push | 0d | 4d | | Open issues (now) | 56 | 10 | | Stars delta | +96 (30d) | +5.2k (30d) | | Open issues delta | +39 (30d) | -3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/modernrelay-omnigraph/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Decision facts: omnigraph - **Adopt for:** Omnigraph is a graph engine designed for lakehouse environments, featuring git-style workflows for managing graph data. It supports operations on knowledge graphs and graph databases, and integrates with technologies, as ## Decision facts: awesome-llm-apps - **Pricing:** freemium - Free with open-source licensing, but commercial exploitation is allowed. - **Adopt for:** awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. - **License detail:** The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. ## Choose when ### Choose omnigraph if… - omnigraph is primarily Rust; awesome-llm-apps is Python. - License: omnigraph is MIT, awesome-llm-apps is Apache-2.0. - Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database. - omnigraph ships Docker support for self-hosted deployment. - When you need a graph engine that integrates seamlessly with lakehouse environments, such as those using Apache Arrow, DataFusion, and S3. ### Choose awesome-llm-apps if… - awesome-llm-apps is primarily Python; omnigraph is Rust. - License: awesome-llm-apps is Apache-2.0, omnigraph is MIT. - Pricing: Free with open-source licensing, but commercial exploitation is allowed.. - Tags unique to awesome-llm-apps: agents, applications, customizable, deployable. - Also covers AI Agents. - When you need quick implementations of various real-world use cases for AI Agents and RAG. ## When NOT to use omnigraph - If your project does not require integration with lakehouse technologies like Apache Arrow, DataFusion, or S3, Omnigraph might not be the best fit. - If your team is not familiar with Rust or prefers a different programming language, Omnigraph's Rust foundation might pose a learning curve or preference mismatch. - For projects that do not benefit from git-style workflows for graph data management, Omnigraph's unique approach might add unnecessary complexity. ## When NOT to use awesome-llm-apps - If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. - When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ## Common questions ### What is the difference between omnigraph and awesome-llm-apps? omnigraph: Lakehouse native graph engine with git-style workflows. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories. ### When should I choose omnigraph over awesome-llm-apps? Choose omnigraph over awesome-llm-apps when omnigraph is primarily Rust; awesome-llm-apps is Python; License: omnigraph is MIT, awesome-llm-apps is Apache-2.0; Tags unique to omnigraph: apache-arrow, context-graph, datafusion, graph-database; omnigraph ships Docker support for self-hosted deployment; When you need a graph engine that integrates seamlessly with lakehouse environments, such as those using Apache Arrow, DataFusion, and S3. ### When should I choose awesome-llm-apps over omnigraph? Choose awesome-llm-apps over omnigraph when awesome-llm-apps is primarily Python; omnigraph is Rust; License: awesome-llm-apps is Apache-2.0, omnigraph is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers AI Agents; When you need quick implementations of various real-world use cases for AI Agents and RAG. ### When should I avoid omnigraph? If your project does not require integration with lakehouse technologies like Apache Arrow, DataFusion, or S3, Omnigraph might not be the best fit. If your team is not familiar with Rust or prefers a different programming language, Omnigraph's Rust foundation might pose a learning curve or preference mismatch. For projects that do not benefit from git-style workflows for graph data management, Omnigraph's unique approach might add unnecessary complexity. ### When should I avoid awesome-llm-apps? If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ### Is omnigraph or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (136,444 vs 1,136). Stars measure visibility, not whether either tool fits your constraints. ### Are omnigraph and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (omnigraph: MIT, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to omnigraph or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [omnigraph alternatives](/tools/modernrelay-omnigraph/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([omnigraph markdown twin](/tools/modernrelay-omnigraph/alternatives.md), [awesome-llm-apps markdown twin](/tools/shubhamsaboo-awesome-llm-apps/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/modernrelay-omnigraph-vs-shubhamsaboo-awesome-llm-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, omnigraph or awesome-llm-apps? omnigraph: Very active. awesome-llm-apps: 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 omnigraph and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [omnigraph trust report](/tools/modernrelay-omnigraph/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=modernrelay-omnigraph`](/api/graphcanon/graph?tool=modernrelay-omnigraph) - 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/_