Dafthunk vs Flowise
Dafthunk is an MIT-licensed workflow automation platform that runs on Cloudflare Workers. Workflows scale to zero, state lives in D1 and R2, and any node can become a tool for an AI agent. Start on our hosted SaaS, or self-host on your own Cloudflare account under MIT. Flowise is a Node.js visual builder for LangChain and LlamaIndex flows, run as a long-running server. Both are JavaScript runtimes, but Dafthunk is serverless and broader in scope.
What Flowise does well
Flowise is a Node.js visual builder for LangChain and LlamaIndex. It exposes chains, agents, retrievers, and memory as drag-and-drop nodes, supports chatbots and RAG apps, and ships with a managed Flowise Cloud. The community is active, and the LangChain and LlamaIndex node libraries stay current with the wider ecosystem.
Where Dafthunk is different
| Dafthunk | Flowise | |
|---|---|---|
License | MIT. Full freedom to fork, embed in a commercial product, or resell a hosted version. | Apache 2.0. Permissive, but the trademark and branding belong to FlowiseAI. |
Runtime | Cloudflare Workers and Cloudflare Workflows. Serverless, scales to zero, durable long-running execution through Workflows. | Long-running Node.js server. Self-hosting needs a VPS, Docker host, or Kubernetes cluster running 24/7. |
Scope | General workflow automation. HTTP, webhook, cron, email, and queue triggers. Nodes for AI, browser, geo, media, data transforms, and protocols. | Focused on LLM chains, agents, and chatbots. Non-AI automation such as cron jobs, email parsing, or SaaS integrations sits outside the primary scope. |
Data layer | Built-in D1 (SQL), R2 (object storage), Vectorize, and Workers AI. Nothing external to provision. | External SQL database, external vector store such as Pinecone, Weaviate, or Qdrant, and external object storage. |
Durability | Cloudflare Workflows provide durable, replayable execution with auto-retries and survival across restarts. | Flows run in a single Node.js process. Long-running or stateful flows depend on external queues and storage. |
Agentic workflows | Any node in the graph can be exposed as a tool for an AI agent. Bindings for Workers AI, OpenAI, Anthropic, and Gemini ship built in. | Agent and tool abstractions are provided by LangChain and LlamaIndex nodes. |
Questions people ask before switching
Can I try Dafthunk without setting up Cloudflare?
Yes. Our hosted SaaS is the fastest way to start and runs the same MIT-licensed code as the open-source project. Self-hosting on your own Cloudflare account is available when you need full control over data, secrets, or infrastructure. You can move between the two at any time.
Is there a Cloudflare-native alternative to Flowise?
Yes. Dafthunk runs on Cloudflare Workers and Workflows, stores data in D1 and R2, and calls Workers AI for inference. Flowise runs as a long-running Node.js server with external databases and vector stores. If your infrastructure is Cloudflare, Dafthunk is the native option.
Can I run Flowise on Cloudflare Workers?
Not cleanly. Flowise is a Node.js server built for a long-running process with filesystem access and background workers. Cloudflare Workers use a different runtime model. Dafthunk was built for Workers from day one.
How does Dafthunk differ from Flowise in license?
Flowise is Apache 2.0, which is permissive but keeps the Flowise trademark and branding with FlowiseAI. Dafthunk is MIT throughout, with no trademark carve-outs and no enterprise tier. You can fork, embed, or resell without friction.
Which is better for chatbots and RAG apps?
Flowise is purpose-built for chatbots and RAG with a UI that matches the LangChain and LlamaIndex primitives. Dafthunk supports RAG through vector search nodes, Cloudflare Vectorize, and AutoRAG, but the product is broader. If your goal is only a chatbot, Flowise covers it faster. If you want agents that reach into browser, geo, media, and SaaS nodes, Dafthunk covers more.
What about production cost?
Flowise needs a server running 24/7, plus an external database and a vector store. Dafthunk runs on Workers and scales to zero, so idle workflows cost nothing. Active costs stay in pennies per thousand executions for most workloads.
When is Flowise still the better choice?
Pick Flowise if you are building a chatbot or RAG app around LangChain or LlamaIndex, you already have a Node.js host, and you want a visual layer that tracks those libraries closely.
Sources
Try Dafthunk
Start on our hosted SaaS and build your first workflow in about four minutes. Self-host on your own Cloudflare account under MIT whenever you need full control.