--- title: "whodb vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/clidey-whodb-vs-shubhamsaboo-awesome-llm-apps" tools: ["clidey-whodb", "shubhamsaboo-awesome-llm-apps"] --- # whodb vs awesome-llm-apps *GraphCanon updated Sep 20, 2026* ## Verdict Pick whodb if whodb offers database exploration with AI integration for multiple databases including ClickHouse, Elasticsearch, MariaDB, MongoDB, MySQL, PostgreSQL, and SQLite3; 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 practical use cases in Python. [whodb](https://whodb.com) reports 5.0k GitHub stars, 240 forks, and 32 open issues, last pushed Sep 20, 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 [whodb's repository](https://github.com/clidey/whodb) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [whodb](/tools/clidey-whodb.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | Where data access meets operational intelligence | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 5,033 | 136,444 | | Forks | 240 | 20,078 | | Open issues | 32 | 10 | | Language | Go | Python | | Adopt for | Whodb offers database exploration with AI integration for multiple databases including ClickHouse, Elasticsearch, MariaDB, MongoDB, MySQL, PostgreSQL, and SQLite3. | 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 | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whodb](/tools/clidey-whodb.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Days since push | 0d | 4d | | Open issues (now) | 32 | 10 | | Stars delta | +26 (30d) | +5.2k (30d) | | Open issues delta | +12 (30d) | -3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/clidey-whodb/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Shared compatibility - **Node.js**: [whodb](/tools/clidey-whodb.md) - Node.js runtime; [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - Node.js runtime ## Decision facts: whodb - **Adopt for:** Whodb offers database exploration with AI integration for multiple databases including ClickHouse, Elasticsearch, MariaDB, MongoDB, MySQL, PostgreSQL, and SQLite3. ## 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 whodb if… - whodb is primarily Go; awesome-llm-apps is Python. - Tags unique to whodb: anthropic, clickhouse, data-analysis, data-visualization. - Suitable for developers and small teams looking for a free production-grade tool ### Choose awesome-llm-apps if… - awesome-llm-apps is primarily Python; whodb is Go. - 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 whodb - Not recommended if your project is incompatible with Apache-2.0 licensing - Avoid if you require per-seat pricing that Whodb does not offer across any plans - Skipping competitors with more customized AI integrations beyond the support for tools like Ollama, Anthropic, or OpenAI ## 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 whodb and awesome-llm-apps? whodb: Where data access meets operational intelligence. 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 whodb over awesome-llm-apps? Choose whodb over awesome-llm-apps when whodb is primarily Go; awesome-llm-apps is Python; Tags unique to whodb: anthropic, clickhouse, data-analysis, data-visualization; Suitable for developers and small teams looking for a free production-grade tool. ### When should I choose awesome-llm-apps over whodb? Choose awesome-llm-apps over whodb when awesome-llm-apps is primarily Python; whodb is Go; 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 whodb? Not recommended if your project is incompatible with Apache-2.0 licensing Avoid if you require per-seat pricing that Whodb does not offer across any plans Skipping competitors with more customized AI integrations beyond the support for tools like Ollama, Anthropic, or OpenAI ### 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 whodb or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (136,444 vs 5,033). Stars measure visibility, not whether either tool fits your constraints. ### Are whodb and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (whodb: Apache-2.0, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to whodb or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [whodb alternatives](/tools/clidey-whodb/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([whodb markdown twin](/tools/clidey-whodb/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/clidey-whodb-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, whodb or awesome-llm-apps? whodb: 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 whodb and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whodb trust report](/tools/clidey-whodb/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=clidey-whodb`](/api/graphcanon/graph?tool=clidey-whodb) - 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/_