Pathway vs RAGFlow

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Pathway RAG	RAGFlow RAG
Tagline	Live data framework for production RAG and streaming ETL pipelines in Python.	Open-source RAG engine with deep document parsing, hybrid search, and visual agent orchestration.
Category	RAG	RAG
Pricing	Freemium· Community free (BSL 1.1, 8GB/4 cores); Scale and Enterprise tiers with license key	Freemium· Free tier; Starter $29/mo; Pro $129/mo; Enterprise custom
Model	Multi-model	Multi-model
Editorial score	7.3 / 10	8.1 / 10
Use cases	live-ragstreaming-etldocument-indexingmultimodal-raganomaly-detection	document-qaenterprise-searchagent-orchestrationknowledge-basehybrid-retrieval
Pros	Genuinely live indexing - documents update without rebuild jobs Self-hosted under BSL 1.1, no data leaves your infra Rich connector library (Kafka, S3, SharePoint, Postgres, Delta Lake) Same pipeline handles batch and streaming 20+ production-ready templates including multimodal and adaptive RAG	Strong deep-document parsing for messy PDFs, tables, and scans Hybrid vector + BM25 retrieval with citation-grounded answers Fully open-source with active GitHub repo and self-host option Visual agent builder plus MCP integration for tool-calling clients Model-agnostic; works with most major LLM providers
Cons	Steeper learning curve than prompt-chain frameworks BSL is not OSI-approved - commercial restrictions apply at scale Smaller community than LangChain/LlamaIndex Pricing for Scale/Enterprise tiers not transparent	Free tier blocks API access, pushing real use to paid plans Self-hosting is non-trivial and resource-hungry Documentation and UI lag behind the engine's capabilities
Website	pathway.com	ragflow.io

Pick Pathway if

✅ Genuinely live indexing - documents update without rebuild jobs
✅ Self-hosted under BSL 1.1, no data leaves your infra
✅ Rich connector library (Kafka, S3, SharePoint, Postgres, Delta Lake)
✅ Same pipeline handles batch and streaming

Pick RAGFlow if

✅ Strong deep-document parsing for messy PDFs, tables, and scans
✅ Hybrid vector + BM25 retrieval with citation-grounded answers
✅ Fully open-source with active GitHub repo and self-host option
✅ Visual agent builder plus MCP integration for tool-calling clients

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