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AFFiNE vs Langfuse

Langfuse offers LLM observability; AFFiNE provides AI assistance for content creation, not analytics.

Side by side

What it is
AFFiNE:AFFiNE is an open-source, local-first knowledge workspace that merges docs, whiteboards, databases and AI.
Langfuse:Langfuse is an open-source platform for tracing, evaluating and monitoring LLM applications and AI agents.
Best for
AFFiNE:All-in-one knowledge OS
Langfuse:LLM observability & analytics
Who it’s for
AFFiNE:Teams and individuals needing an integrated note-taking, planning and visual collaboration tool.
Langfuse:Developers building, debugging and scaling LLM-based apps and agents.
Pricing
AFFiNE:Freemium
Langfuse:Freemium
Plans
AFFiNE:Free (Cloud) Free · Pro $6.75 per month · Team $10 per seat per month · Believer $499.99 · AFFiNE AI Add-on $8.9 per month billed annually
Langfuse:Hobby Free · Core $29 per month · Pro $199 per month · Enterprise $2499 per month
Open source
AFFiNE:Yes, 73,041 GitHub stars
Langfuse:Yes, 35,097 GitHub stars
Works with
AFFiNE:—
Langfuse:Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift
DevHunt upvotes
AFFiNE:5
Langfuse:89
Launched on DevHunt
AFFiNE:Apr 2025
Langfuse:Jan 2023

AFFiNE features

  • Unified Docs & Whiteboards. Write, draw and organize content on a single canvas without switching tools.
  • AI Copilot. Generate, rewrite, translate and summarize content directly inside AFFiNE.
  • Kanban & Project Boards. Track tasks, milestones and workflows with built-in Kanban views.
  • Local-First & Privacy-Focused. Data lives on the user’s device with optional cloud sync for control.
  • Templates & Moodboards. Ready-made templates for planners, storyboards, knowledge bases and more.
  • Real-time Collaboration. Edit docs and whiteboards together with live sync and version history.
  • Self-Hosted & Cloud Options. Run the full stack on your own servers or use AFFiNE Cloud hosting.
  • Open-Source MIT Editor. The editor is MIT-licensed, allowing unlimited customization.

Langfuse features

  • Hierarchical Traces. Capture every LLM call, tool invocation and retrieval step with filters for user, session, cost and latency.
  • Prompt Management. Version, fetch, release and cache prompts separately from code with one-click deployments.
  • Evaluation Engine. Run LLM-as-judge, heuristic or human-review evaluations on production data or experiments.
  • Experiments & Datasets. Define test cases, run experiments and create golden datasets for continuous improvement.
  • Dashboards & Alerts. Monitor cost, latency and quality via custom dashboards and automated alerts.
  • Human Annotation. Collaborative human-in-the-loop workflows with annotation queues.
  • Extensive Integrations. Supports Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift and 100+ agent frameworks and model providers.
  • Self-hosted & Cloud Options. Available as hosted SaaS or self-hosted under MIT license.

Based on each tool's website and DevHunt data. Details may change; check the official sites.