--- title: "ploomber vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ploomber-ploomber-vs-shubhamsaboo-awesome-llm-apps" tools: ["ploomber-ploomber", "shubhamsaboo-awesome-llm-apps"] --- # ploomber vs awesome-llm-apps *GraphCanon updated Jul 11, 2026* ## Verdict Pick ploomber when tags unique to ploomber: data-engineering, data-science, jupyter, jupyter-notebooks; pick awesome-llm-apps when pricing: Free with open-source licensing, but commercial exploitation is allowed.. [ploomber](https://docs.ploomber.io) reports 3.6k GitHub stars, 242 forks, and 110 open issues, last pushed May 29, 2025. [awesome-llm-apps](https://www.theunwindai.com) has 118k stars, 17k forks, and 6 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [ploomber's repository](https://github.com/ploomber/ploomber) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [ploomber](/tools/ploomber-ploomber.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️ | 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. | | Stars | 3,622 | 117,774 | | Forks | 242 | 17,498 | | Open issues | 110 | 6 | | Language | Python | Python | | 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. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | 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, Inference & Serving | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ploomber](/tools/ploomber-ploomber.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 408d | 0d | | Archived on GitHub | Yes | No | | Open issues (now) | 110 | 6 | | Owner type | Organization | User | | Full report | [trust report](/tools/ploomber-ploomber/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Shared compatibility - **Python**: [ploomber](/tools/ploomber-ploomber.md) - Python runtime; [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - Python runtime ## 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 ploomber if… - Tags unique to ploomber: data-engineering, data-science, jupyter, jupyter-notebooks. - Also covers Inference & Serving. ### Choose awesome-llm-apps if… - 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 ploomber - ploomber is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## 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 ploomber and awesome-llm-apps? ploomber: The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️. awesome-llm-apps: 100+ AI Agent & RAG apps you can actually run — clone, customize, ship.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ploomber over awesome-llm-apps? Choose ploomber over awesome-llm-apps when Tags unique to ploomber: data-engineering, data-science, jupyter, jupyter-notebooks; Also covers Inference & Serving. ### When should I choose awesome-llm-apps over ploomber? Choose awesome-llm-apps over ploomber when 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 ploomber? ploomber is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### 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 ploomber or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (117,774 vs 3,622). Stars measure visibility, not whether either tool fits your constraints. ### Are ploomber and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (ploomber: Apache-2.0, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to ploomber or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [ploomber alternatives](/tools/ploomber-ploomber/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([ploomber markdown twin](/tools/ploomber-ploomber/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/ploomber-ploomber-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, ploomber or awesome-llm-apps? ploomber: Archived. 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 ploomber and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ploomber trust report](/tools/ploomber-ploomber/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ploomber-ploomber`](/api/graphcanon/graph?tool=ploomber-ploomber) - 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/_