--- title: "databerry vs anything-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gmpetrov-databerry-vs-mintplex-labs-anything-llm" tools: ["gmpetrov-databerry", "mintplex-labs-anything-llm"] --- # databerry vs anything-llm *GraphCanon updated Sep 20, 2026* ## Verdict Pick databerry if suitable for users looking to develop custom LLM agents without coding expertise; pick anything-llm if anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. [databerry](https://chaindesk.ai) reports 3.0k GitHub stars, 415 forks, and 166 open issues, last pushed Jun 17, 2024. [anything-llm](https://anythingllm.com) has 66k stars, 7.3k forks, and 315 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [databerry's repository](https://github.com/gmpetrov/databerry) and [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm). | | [databerry](/tools/gmpetrov-databerry.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Tagline | The no-code platform for building custom LLM Agents | Self-hosted AI agent experience | | Stars | 2,966 | 66,167 | | Forks | 415 | 7,349 | | Open issues | 166 | 315 | | Language | - | JavaScript | | Adopt for | Suitable for users looking to develop custom LLM agents without coding expertise. | anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. | | Persona | - | - | | Runtime | - | - | | License | - | MIT License, allowing for free use, modification, and distribution. | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [databerry](/tools/gmpetrov-databerry.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 824d | 0d | | Open issues (now) | 166 | 315 | | Stars delta | +1 (30d) | +1.5k (30d) | | Open issues delta | 0 (30d) | -4 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/gmpetrov-databerry/trust.md) | [trust report](/tools/mintplex-labs-anything-llm/trust.md) | ## Decision facts: databerry - **Adopt for:** Suitable for users looking to develop custom LLM agents without coding expertise. ## Decision facts: anything-llm - **Pricing:** freemium - Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment. - **Adopt for:** anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. - **License detail:** MIT License, allowing for free use, modification, and distribution. ## Choose when ### Choose databerry if… - Tags unique to databerry: ai, aichatbot, chatbot, llm. - When you have non-technical team members who need to craft and deploy specific AI chatbot functionalities. - Leaner open-issue backlog (166). ### Choose anything-llm if… - Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure.. - Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment.. - Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai. - Also covers Inference & Serving. - When you need a local-first AI agent experience that you can fully control and customize. ## When NOT to use databerry - If you are a seasoned developer looking for customizable control over agent functions beyond no-code capabilities. - In scenarios requiring integration with complex, non-standard APIs or systems that cannot be managed on a no-code platform. ## When NOT to use anything-llm - If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management. - When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity. ## Common questions ### What is the difference between databerry and anything-llm? databerry: The no-code platform for building custom LLM Agents. anything-llm: Self-hosted AI agent experience. See the comparison table for live GitHub stats and shared categories. ### When should I choose databerry over anything-llm? Choose databerry over anything-llm when Tags unique to databerry: ai, aichatbot, chatbot, llm; When you have non-technical team members who need to craft and deploy specific AI chatbot functionalities; Leaner open-issue backlog (166). ### When should I choose anything-llm over databerry? Choose anything-llm over databerry when Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure.; Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment.; Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai; Also covers Inference & Serving; When you need a local-first AI agent experience that you can fully control and customize. ### When should I avoid databerry? If you are a seasoned developer looking for customizable control over agent functions beyond no-code capabilities. In scenarios requiring integration with complex, non-standard APIs or systems that cannot be managed on a no-code platform. ### When should I avoid anything-llm? If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management. When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity. ### Is databerry or anything-llm more popular on GitHub? anything-llm has more GitHub stars (66,167 vs 2,966). Stars measure visibility, not whether either tool fits your constraints. ### Are databerry and anything-llm open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to databerry or anything-llm? GraphCanon lists graph-backed alternatives at [databerry alternatives](/tools/gmpetrov-databerry/alternatives) and [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) ([databerry markdown twin](/tools/gmpetrov-databerry/alternatives.md), [anything-llm markdown twin](/tools/mintplex-labs-anything-llm/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/gmpetrov-databerry-vs-mintplex-labs-anything-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, databerry or anything-llm? databerry: Dormant. anything-llm: 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 databerry and anything-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [databerry trust report](/tools/gmpetrov-databerry/trust); [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gmpetrov-databerry`](/api/graphcanon/graph?tool=gmpetrov-databerry) - 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/_