--- title: "phoenix vs openllmetry" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arize-ai-phoenix-vs-traceloop-openllmetry" tools: ["arize-ai-phoenix", "traceloop-openllmetry"] --- # phoenix vs openllmetry Neutral, constraint-first comparison with live GitHub stats. | | [phoenix](/tools/arize-ai-phoenix.md) | [openllmetry](/tools/traceloop-openllmetry.md) | | --- | --- | --- | | Tagline | AI Observability & Evaluation | Open-source observability for your LLM application | | Stars | 10,453 | 7,281 | | Forks | 962 | 1,016 | | Open issues | 650 | 591 | | Language | Python | Python | | Adopt for | - | OpenLLMetry is an open-source observability tool based on OpenTelemetry for monitoring and metrics in GenAI and LLM applications. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 license grants permission to use, study, modify, and distribute the tool freely. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [phoenix](/tools/arize-ai-phoenix.md) | [openllmetry](/tools/traceloop-openllmetry.md) | | --- | --- | --- | | Open issues (now) | 650 | 591 | | Security scan | 2 low (2 low) | 29 low (29 low) | | Full report | [trust report](/tools/arize-ai-phoenix/trust.md) | [trust report](/tools/traceloop-openllmetry/trust.md) | **Typed relationship:** phoenix _(related)_ openllmetry ## Decision facts: openllmetry - **Requirements:** Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb - **Adopt for:** OpenLLMetry is an open-source observability tool based on OpenTelemetry for monitoring and metrics in GenAI and LLM applications. - **License detail:** Apache-2.0 license grants permission to use, study, modify, and distribute the tool freely. ## Choose when ### Choose phoenix if… - License: phoenix is Other, openllmetry is Apache-2.0. - Graph edge: phoenix is a typed related of openllmetry - see the relationship row above. - Tags unique to phoenix: smolagents, agents, ai-monitoring, evals. - phoenix ships Docker support for self-hosted deployment. ### Choose openllmetry if… - License: openllmetry is Apache-2.0, phoenix is Other. - Requirements: Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb. - Graph edge: openllmetry is a typed related of phoenix - see the relationship row above. - Tags unique to openllmetry: llmops, ml, artifical-intelligence, llm. - - Use it if you are working with Large Language Model (LLM) or Generative AI applications that require detailed observations, including model oversight and performance metrics. ## When NOT to use phoenix - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use openllmetry - - Avoid using it for applications where existing comprehensive proprietary observability solutions already meet all requirements without the need for integration flexibility offered by OpenTelemetry. - - Not recommended if your team has limited experience with OpenTelemetry, which could complicate adoption and integration with other tools unless there is a dedicated effort to adapt. ## Common questions ### What is the difference between phoenix and openllmetry? phoenix: AI Observability & Evaluation. openllmetry: Open-source observability for your LLM application. See the comparison table for live GitHub stats and shared categories. ### When should I choose phoenix over openllmetry? Choose phoenix over openllmetry when License: phoenix is Other, openllmetry is Apache-2.0; Graph edge: phoenix is a typed related of openllmetry - see the relationship row above; Tags unique to phoenix: smolagents, agents, ai-monitoring, evals; phoenix ships Docker support for self-hosted deployment. ### When should I choose openllmetry over phoenix? Choose openllmetry over phoenix when License: openllmetry is Apache-2.0, phoenix is Other; Requirements: Built on top of OpenTelemetry; compatible with various observability solutions like Datadog and Honeycomb; Graph edge: openllmetry is a typed related of phoenix - see the relationship row above; Tags unique to openllmetry: llmops, ml, artifical-intelligence, llm; - Use it if you are working with Large Language Model (LLM) or Generative AI applications that require detailed observations, including model oversight and performance metrics. ### When should I avoid phoenix? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid openllmetry? - Avoid using it for applications where existing comprehensive proprietary observability solutions already meet all requirements without the need for integration flexibility offered by OpenTelemetry. - Not recommended if your team has limited experience with OpenTelemetry, which could complicate adoption and integration with other tools unless there is a dedicated effort to adapt. ### Is phoenix or openllmetry more popular on GitHub? phoenix has more GitHub stars (10,453 vs 7,281). Stars measure visibility, not whether either tool fits your constraints. ### Are phoenix and openllmetry open source? Yes - both are open-source projects on GitHub (phoenix: Other, openllmetry: Apache-2.0). ### Where can I find alternatives to phoenix or openllmetry? GraphCanon lists graph-backed alternatives at /tools/arize-ai-phoenix/alternatives and /tools/traceloop-openllmetry/alternatives (/tools/arize-ai-phoenix/alternatives.md, /tools/traceloop-openllmetry/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 /compare/arize-ai-phoenix-vs-traceloop-openllmetry.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, phoenix or openllmetry? phoenix: Very active. openllmetry: 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 phoenix and openllmetry? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: phoenix: /tools/arize-ai-phoenix/trust; openllmetry: /tools/traceloop-openllmetry/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arize-ai-phoenix`](/api/graphcanon/graph?tool=arize-ai-phoenix) - 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/_