Learn how Laminar 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
2 days agoRepository age
2 yearsVersion
v0.3.3License
Apache-2.0Self-hosted
YesRepository
lmnr-ai/lmnr
Last 30 days
Last commit
13 hours agoRepository age
3 yearsVersion
v4.76.0License
MITSelf-hosted
YesRepository
langfuse/langfuse
Langfuse appears to have several advantages over Laminar, particularly in popularity, growth, maturity and licensing. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Langfuse significantly outpaces Laminar in community adoption with 37,139 stars compared to 3,478 stars on GitHub. This 10.7x difference suggests Langfuse has a much larger and more active community. In terms of developer contributions, Langfuse has 4,171 forks, indicating strong developer engagement.
Langfuse is growing faster, adding 1,565 stars in the last 30 days (+4.4%) against adding 111 stars for Laminar (+3.3%). Langfuse is both larger and pulling further ahead.
Both projects show recent activity, with Laminar last updated 2 days ago and Langfuse 13 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Typescript, JSX, Next.js. However, they differ in their additional technology choices: Laminar uses Python, Rust while Langfuse leverages Bash.
Langfuse has been in development longer, starting 3 years ago, compared to Laminar which began 2 years ago. This 1.3-year head start suggests Langfuse may have more mature features and established processes.
Langfuse uses the MIT license, which is more permissive than Laminar's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in LLM Observability & Evaluation.
Both Laminar and Langfuse offer self-hosting capabilities, giving you full control over your data and infrastructure.