--- title: "databerry vs lmnr" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gmpetrov-databerry-vs-lmnr-ai-lmnr" tools: ["gmpetrov-databerry", "lmnr-ai-lmnr"] --- # databerry vs lmnr *GraphCanon updated Jul 12, 2026* ## Verdict Pick databerry when tags unique to databerry: aichatbot, chatbot, chatbots, chatgpt; pick lmnr when pricing: Open-source (Apache-2.0 license) with options for managed platforms which likely carry additional costs not specified in the repository content.. [databerry](https://chaindesk.ai) reports 3.0k GitHub stars, 422 forks, and 166 open issues, last pushed Jun 17, 2024. [lmnr](https://laminar.sh) has 3.1k stars, 217 forks, and 92 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [databerry's repository](https://github.com/gmpetrov/databerry) and [lmnr's repository](https://github.com/lmnr-ai/lmnr). | | [databerry](/tools/gmpetrov-databerry.md) | [lmnr](/tools/lmnr-ai-lmnr.md) | | --- | --- | --- | | Tagline | The no-code platform for building custom LLM Agents | Laminar - open-source observability platform purpose-built for AI agents. YC S24. | | Stars | 2,960 | 3,085 | | Forks | 422 | 217 | | Open issues | 166 | 92 | | Language | - | TypeScript | | Adopt for | - | Laminar (lmnr) is an open-source observability platform for AI agents with features allowing both self-hosted and managed deployment options. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [databerry](/tools/gmpetrov-databerry.md) | [lmnr](/tools/lmnr-ai-lmnr.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 753d | 0d | | Open issues (now) | 166 | 92 | | Owner type | User | Organization | | Full report | [trust report](/tools/gmpetrov-databerry/trust.md) | [trust report](/tools/lmnr-ai-lmnr/trust.md) | ## Decision facts: lmnr - **Pricing:** freemium - Open-source (Apache-2.0 license) with options for managed platforms which likely carry additional costs not specified in the repository content. - **Requirements:** Requires Docker; Laminar supports both self-hosting via Docker Compose and managed deployments, so users must ensure they have Docker installed for self-hosted setups. - **Adopt for:** Laminar (lmnr) is an open-source observability platform for AI agents with features allowing both self-hosted and managed deployment options. ## Choose when ### Choose databerry if… - Tags unique to databerry: aichatbot, chatbot, chatbots, chatgpt. ### Choose lmnr if… - Pricing: Open-source (Apache-2.0 license) with options for managed platforms which likely carry additional costs not specified in the repository content.. - Requirements: Requires Docker; Laminar supports both self-hosting via Docker Compose and managed deployments, so users must ensure they have Docker installed for self-hosted setups.. - Tags unique to lmnr: agent-observability, agents, ai-observability, aiops. - Also covers Developer Tools. - lmnr ships Docker support for self-hosted deployment. - You need a specialized tool for monitoring and evaluating the performance of your AI agents in either self-hosted or managed environments. ## When NOT to use databerry - Last GitHub push was 755 days ago (dormant maintenance, Jun 17, 2024). Validate activity before betting a new project on databerry. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use lmnr - If you prefer solutions that require minimal setup or configuration beyond what is provided by out-of-the-box platforms and do not have the resources to manage a self-hosted environment. - Your project has firm constraints against using TypeScript or Rust, as Laminar primarily supports these technologies for its platform integrations. ## Common questions ### What is the difference between databerry and lmnr? databerry: The no-code platform for building custom LLM Agents. lmnr: Laminar - open-source observability platform purpose-built for AI agents. YC S24.. See the comparison table for live GitHub stats and shared categories. ### When should I choose databerry over lmnr? Choose databerry over lmnr when Tags unique to databerry: aichatbot, chatbot, chatbots, chatgpt. ### When should I choose lmnr over databerry? Choose lmnr over databerry when Pricing: Open-source (Apache-2.0 license) with options for managed platforms which likely carry additional costs not specified in the repository content.; Requirements: Requires Docker; Laminar supports both self-hosting via Docker Compose and managed deployments, so users must ensure they have Docker installed for self-hosted setups.; Tags unique to lmnr: agent-observability, agents, ai-observability, aiops; Also covers Developer Tools; lmnr ships Docker support for self-hosted deployment; You need a specialized tool for monitoring and evaluating the performance of your AI agents in either self-hosted or managed environments. ### When should I avoid databerry? Last GitHub push was 755 days ago (dormant maintenance, Jun 17, 2024). Validate activity before betting a new project on databerry. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid lmnr? If you prefer solutions that require minimal setup or configuration beyond what is provided by out-of-the-box platforms and do not have the resources to manage a self-hosted environment. Your project has firm constraints against using TypeScript or Rust, as Laminar primarily supports these technologies for its platform integrations. ### Is databerry or lmnr more popular on GitHub? lmnr has more GitHub stars (3,085 vs 2,960). Stars measure visibility, not whether either tool fits your constraints. ### Are databerry and lmnr open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to databerry or lmnr? GraphCanon lists graph-backed alternatives at [databerry alternatives](/tools/gmpetrov-databerry/alternatives) and [lmnr alternatives](/tools/lmnr-ai-lmnr/alternatives) ([databerry markdown twin](/tools/gmpetrov-databerry/alternatives.md), [lmnr markdown twin](/tools/lmnr-ai-lmnr/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-lmnr-ai-lmnr.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, databerry or lmnr? databerry: Dormant. lmnr: 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 lmnr? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [databerry trust report](/tools/gmpetrov-databerry/trust); [lmnr trust report](/tools/lmnr-ai-lmnr/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/_