Learn how Laminar and LangWatch 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
3 hours agoRepository age
2 yearsVersion
v0.3.2License
Apache-2.0Self-hosted
YesRepository
lmnr-ai/lmnr
Last 30 days
Last commit
2 hours agoRepository age
3 yearsVersion
3.21.0License
Apache-2.0Repository
langwatch/langwatch
Laminar appears to have several advantages over LangWatch, particularly in growth and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Both tools have similar popularity levels, with Laminar having 3,438 stars and LangWatch having 4,991 stars on GitHub. In terms of developer contributions, LangWatch has 417 forks, indicating moderate developer engagement.
Laminar is growing faster, adding 161 stars in the last 30 days (+4.9%) against adding 119 stars for LangWatch (+2.4%). Laminar is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with Laminar last updated 3 hours ago and LangWatch 2 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Typescript, JSX, Python. However, they differ in their additional technology choices: Laminar uses Next.js, Rust while LangWatch leverages Bash, Golang, SCSS, Ruby.
Both projects started around the same time, with Laminar beginning 2 years ago and LangWatch 3 years ago.
Both projects use the Apache-2.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in LLM Observability & Evaluation.
Laminar provides self-hosting options for complete data control and customization, while LangWatch may be primarily cloud-based or require different deployment approaches.