Learn how Arize Phoenix and Langfuse differ in their key features, development activity, technology stack and community adoption, so you can decide which of these llm observability & evaluation is best for you.
Last 30 days
Last commit
21 hours agoRepository age
4 yearsVersion
1.20.1License
Elastic-2.0Self-hosted
YesRepository
arize-ai/phoenix
Last 30 days
Last commit
5 hours agoRepository age
3 yearsVersion
v4.76.0License
MITSelf-hosted
YesRepository
langfuse/langfuse
Langfuse appears to have several advantages over Arize Phoenix, particularly in popularity, growth and licensing. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Langfuse significantly outpaces Arize Phoenix in community adoption with 37,176 stars compared to 12,207 stars on GitHub. This 3.0x difference suggests Langfuse has a much larger and more active community. In terms of developer contributions, Langfuse has 4,182 forks, indicating strong developer engagement.
Langfuse is growing faster, adding 1,564 stars in the last 30 days (+4.4%) against adding 429 stars for Arize Phoenix (+3.6%). Langfuse is both larger and pulling further ahead.
Both projects show recent activity, with Arize Phoenix last updated 21 hours ago and Langfuse 5 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX. However, they differ in their additional technology choices: Arize Phoenix uses Python while Langfuse leverages Next.js.
Both projects started around the same time, with Arize Phoenix beginning 4 years ago and Langfuse 3 years ago.
Langfuse uses the MIT license, which is more permissive than Arize Phoenix's Elastic-2.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in LLM Observability & Evaluation.
Both Arize Phoenix and Langfuse offer self-hosting capabilities, giving you full control over your data and infrastructure.