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Laminar vs Langfuse

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.

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Favicon of Laminar

Laminar

AI
Laminar is an open-source platform that helps collect, understand, and utilize data for building high-quality LLM applications.
3,182stars+80(+2.6%)

Last 30 days

Screenshot of Laminar
Favicon of Langfuse

Langfuse

AI
Langfuse provides tracing, evaluations, prompt management, and analytics to debug and improve LLM applications.
33,392stars+1,889(+6%)

Last 30 days

Screenshot of Langfuse

Detailed Comparison

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 wins
Community & Popularity

Langfuse significantly outpaces Laminar in community adoption with 33,392 stars compared to 3,182 stars on GitHub. This 10.5x difference suggests Langfuse has a much larger and more active community. In terms of developer contributions, Langfuse has 3,593 forks, indicating strong developer engagement.

Langfuse wins
Growth Momentum

Langfuse is growing faster, adding 1,889 stars in the last 30 days (+6%) against adding 80 stars for Laminar (+2.6%). Langfuse is both larger and pulling further ahead.

Comparable
Development Activity

Both projects show recent activity, with Laminar last updated 1 day ago and Langfuse 8 hours ago.

Comparable
Technology Stack

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 wins
Project Maturity

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 wins
Licensing

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.

Comparable
Use Cases & Features

Both tools serve similar use cases in LLM Observability & Evaluation.

Comparable
Hosting & Deployment

Both Laminar and Langfuse offer self-hosting capabilities, giving you full control over your data and infrastructure.