Updated March 2026 DataStax Backed

Dify vs Langflow (2026)

Dify and Langflow are both visual LLM application builders, but they come from different philosophies. Dify is a full-stack AI platform; Langflow is a visual interface for LangChain pipelines.

What Is Langflow?

Langflow is an open-source visual builder for LangChain-based AI applications. It was acquired by DataStax in 2024, which brought commercial backing and a managed cloud offering. With Langflow, you build flows by connecting LangChain components — document loaders, embeddings, LLMs, memory — in a drag-and-drop canvas.

Langflow's cloud (via DataStax) charges $0.02 per flow run — a consumption-based model that can be cheaper than Dify Cloud for low-volume apps, but expensive at scale.

Full Feature Comparison

Feature Dify Langflow
GitHub Stars 134k+ 18k+
Founded / Backing 2023 / Independent 2023 / DataStax
License Apache 2.0 MIT
Built On Standalone platform Built on LangChain
Primary Interface Dashboard + workflow canvas Visual flow editor
Min RAM 4 GB 2 GB
Docker Setup docker-compose (complex) Single container (simple)
RAG / Knowledge Base Advanced built-in Via LangChain loaders
Multi-lingual UI 13+ languages English only
Team Management Yes (workspaces, roles) Limited
Conversation Analytics Yes No
LangChain Integration Via API only Native (core dependency)
Cloud Pricing $59/mo (Pro) $0.02/run (DataStax Cloud)
Production Readiness High Medium

★ indicates the stronger option for that feature

Key Differences

LangChain Dependency

This is the fundamental difference. Langflow is essentially a GUI for LangChain — every component maps to a LangChain class. This is great if you know LangChain, but creates tight coupling and means your flows are dependent on LangChain's API changes.

Dify is framework-agnostic. It connects directly to LLM provider APIs (OpenAI, Anthropic, Ollama, etc.) without LangChain. This makes it more approachable for non-Python developers and more stable as it doesn't inherit LangChain's breaking changes.

Production vs Prototyping

Dify for Production

  • Role-based workspace access
  • API key management per app
  • Conversation logs and analytics
  • Version control for prompts
  • Embeddable widget for end users
  • Usage monitoring and limits

Langflow for Prototyping

  • Rapid flow experimentation
  • Direct LangChain component access
  • Export flows as JSON/Python
  • Great for developer exploration
  • DataStax cloud for easy deployment

Self-Hosting Complexity

Dify — 8 containers

nginx, api, worker, web,
db, redis, weaviate, sandbox

Min: 4 GB RAM, 50 GB disk

Langflow — 2 containers

langflow, postgres
(or SQLite for dev)

Min: 2 GB RAM, 10 GB disk

Community and Support

GitHub Stars 134k+
Dify Discord Active
Tutorials (web) Many
GitHub Stars 18k+
DataStax Support Commercial
Tutorials (web) Growing

Frequently Asked Questions

What is the main difference between Dify and Langflow?

Langflow is built on top of LangChain and focuses on visual prototyping of LangChain pipelines. Dify is a standalone platform for building and deploying production AI applications with broader features including team management, knowledge bases and conversation analytics.

Is Langflow free to self-host?

Yes. Langflow is open-source (MIT license) and free to self-host. DataStax also offers Langflow Cloud with a free tier and usage-based pricing at $0.02 per run.

Which is better for non-LangChain users?

Dify. It is LLM-framework agnostic and connects directly to LLM provider APIs without requiring knowledge of LangChain. Langflow is most useful if you already work within the LangChain ecosystem.

Does Dify have a larger community than Langflow?

Yes. As of March 2026, Dify has over 134k GitHub stars vs Langflow's 18k+. Dify also has a more active Discord community and significantly more third-party tutorials available online.