--- title: "doris vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-doris-vs-shubhamsaboo-awesome-llm-apps" tools: ["apache-doris", "shubhamsaboo-awesome-llm-apps"] --- # doris vs awesome-llm-apps *GraphCanon updated Aug 19, 2026* ## Verdict Pick doris if apache Doris is a real-time analytics and hybrid search database focused on enhancing AI agents through detailed observability and high-performance big data querying; 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. [doris](https://doris.apache.org) reports 16k GitHub stars, 3.9k forks, and 1.3k open issues, last pushed Aug 19, 2026. [awesome-llm-apps](https://www.theunwindai.com) has 131k stars, 19k forks, and 13 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [doris's repository](https://github.com/apache/doris) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [doris](/tools/apache-doris.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | Real-time analytics and hybrid search database for AI agents | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 15,796 | 131,230 | | Forks | 3,913 | 19,346 | | Open issues | 1,257 | 13 | | Language | C++ | Python | | Adopt for | Apache Doris is a real-time analytics and hybrid search database focused on enhancing AI agents through detailed observability and high-performance big data querying. | 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 | AI Agents, Evaluation & Observability | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [doris](/tools/apache-doris.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Days since push | 0d | 4d | | Open issues (now) | 1.3k | 13 | | Stars delta | +164 (30d) | +14k (30d) | | Open issues delta | +150 (30d) | +6 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/apache-doris/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Decision facts: doris - **Adopt for:** Apache Doris is a real-time analytics and hybrid search database focused on enhancing AI agents through detailed observability and high-performance big data querying. ## 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 doris if… - doris is primarily C++; awesome-llm-apps is Python. - Tags unique to doris: agent, ai, bigquery, database. - Also covers Evaluation & Observability. - When you need a system that offers both real-time analytics capabilities and robust search features specifically designed for AI systems, enabling immediate responses to dynamic data changes. ### Choose awesome-llm-apps if… - awesome-llm-apps is primarily Python; doris is C++. - Pricing: Free with open-source licensing, but commercial exploitation is allowed.. - Tags unique to awesome-llm-apps: agents, applications, customizable, deployable. - Also covers Data & Retrieval. - When you need quick implementations of various real-world use cases for AI Agents and RAG. ## When NOT to use doris - If there are strict compliance requirements around third-party dependencies that might not align with the Apache 2.0 License, considering disabling certain features in Doris can be a workaround but is - When an open-source database solution without real-time analytics and hybrid search capabilities meets your needs more efficiently or cost-effectively; Doris's niche focus may result in unnecessary b - If you require immediate compliance with all third-party license requirements without the potential need for feature tweaking, as some components of Apache Doris might necessitate disabling certain of ## 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 doris and awesome-llm-apps? doris: Real-time analytics and hybrid search database for AI agents. 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 doris over awesome-llm-apps? Choose doris over awesome-llm-apps when doris is primarily C++; awesome-llm-apps is Python; Tags unique to doris: agent, ai, bigquery, database; Also covers Evaluation & Observability; When you need a system that offers both real-time analytics capabilities and robust search features specifically designed for AI systems, enabling immediate responses to dynamic data changes. ### When should I choose awesome-llm-apps over doris? Choose awesome-llm-apps over doris when awesome-llm-apps is primarily Python; doris is C++; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers Data & Retrieval; When you need quick implementations of various real-world use cases for AI Agents and RAG. ### When should I avoid doris? If there are strict compliance requirements around third-party dependencies that might not align with the Apache 2.0 License, considering disabling certain features in Doris can be a workaround but is When an open-source database solution without real-time analytics and hybrid search capabilities meets your needs more efficiently or cost-effectively; Doris's niche focus may result in unnecessary b If you require immediate compliance with all third-party license requirements without the potential need for feature tweaking, as some components of Apache Doris might necessitate disabling certain of ### 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 doris or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (131,230 vs 15,796). Stars measure visibility, not whether either tool fits your constraints. ### Are doris and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (doris: Apache-2.0, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to doris or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [doris alternatives](/tools/apache-doris/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([doris markdown twin](/tools/apache-doris/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/apache-doris-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, doris or awesome-llm-apps? doris: 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 doris and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [doris trust report](/tools/apache-doris/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apache-doris`](/api/graphcanon/graph?tool=apache-doris) - 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/_