Overview
Compare Langfuse and Arize Phoenix on LLM observability, trace/prompt management, evaluation capabilities, integration options, and open-source licensing.
TypeScript · NOASSERTION
Open-source LLM engineering platform providing tracing, evaluations, prompt management, and dataset management with integrations for LangChain, OpenAI, Anthropic, and more.
Python · NOASSERTION
Phoenix is an open-source observability and evaluation tool for LLM and agent applications, supporting online tracing and offline diagnosis.
| Best for | Langfuse | Arize Phoenix |
|---|---|---|
| Core positioning | End-to-end LLM observability platform, native OpenTelemetry, prompt/trace/eval suite | Arize's LLM observability and evaluation framework, OpenInference-based, focused on eval and drift detection |
| Best for | Production LLM apps needing trace, prompt versioning, and user feedback loop | LLM teams needing model comparison, embedding visualization, and retrieval quality analysis |
| Learning curve | Medium, OTel decorator integration with a few lines to capture traces, complete UI config | Medium, OpenInference auto-instrumentation, but eval workflow requires span model understanding |
| Ecosystem maturity | Open source (MIT) + commercial cloud edition, YC-backed, fast community growth, integrated with LangChain/LlamaIndex | Maintained by Arize AI, mature commercial Arize AX product, OpenInference adopted by multiple frameworks |
| Integration and deployment | Self-hosted Docker / Kubernetes + managed cloud (US/EU regions), Postgres + ClickHouse backend | Local `pip install arize-phoenix` notebook mode or self-hosted service for production |
| Metric | Langfuse | Arize Phoenix |
|---|---|---|
| Stars | 31.5k | 10.6k |
| Forks | 3.3k | 998 |
| Language | TypeScript | Python |
| License | NOASSERTION | NOASSERTION |
| Last commit | July 20, 2026 | July 21, 2026 |
Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.