Which is more popular, Dify or Langfuse?

Dify has more GitHub stars (157,730 vs 35,301).

Which is more actively developed, Dify or Langfuse?

Dify had more commits in the last 90 days (2,338 vs 2,007).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

Dify is growing faster: +3,652 GitHub stars in the last 30 days vs +1,812 for Langfuse.
Pick Dify for: production-ready platform for agentic workflow development. Pick Langfuse for: open-source LLM engineering platform for observability, evaluation, prompt and dataset management.

From GitHub data refreshed daily.

Production-ready platform for agentic workflow development.

Langfuseopen-source

Open-source LLM engineering platform for observability, evaluation, prompt and dataset management

+Open source with MIT license allowing full customization and transparency, plus active community support
+Comprehensive feature set combining observability, prompt management, evaluations, and datasets in one platform
+Extensive integrations with major LLM frameworks and tools including OpenTelemetry, LangChain, and OpenAI SDK

•Production LLM application monitoring to track performance, costs, and identify issues in real-time
•Prompt engineering and management for teams collaborating on optimizing model prompts and tracking versions
•LLM evaluation and testing to measure model performance across different datasets and use cases

Which is more popular, Dify or Langfuse?: Dify has more GitHub stars (157,730 vs 35,301).
Which is more actively developed, Dify or Langfuse?: Dify had more commits in the last 90 days (2,338 vs 2,007).
Should I use Dify or Langfuse?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.