CocoIndex vs Pathway

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

	CocoIndex RAG	Pathway RAG
Tagline	Open-source incremental data framework that keeps RAG indexes and agent context continuously fresh.	Live data framework for production RAG and streaming ETL pipelines in Python.
Category	RAG	RAG
Pricing	Free· Open-source, self-hosted; bring your own infra	Freemium· Community free (BSL 1.1, 8GB/4 cores); Scale and Enterprise tiers with license key
Model	Bring-your-own (embeddings + LLM)	Multi-model
Editorial score	6.9 / 10	7.3 / 10
Use cases	code-indexingrag-pipelinesagent-contextknowledge-graphssemantic-search	live-ragstreaming-etldocument-indexingmultimodal-raganomaly-detection
Pros	Incremental reprocessing keeps indexes sub-second fresh without full reruns AST-aware code indexing with call graphs, not just naive text chunking Open source and self-hosted; works with Postgres/pgvector Declarative Python API with lineage and schema evolution built in	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
Cons	Self-hosted only - you operate the database, embeddings, and LLM yourself Python-only framework; no managed cloud or hosted UI Younger ecosystem than LlamaIndex or LangChain	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
Website	cocoindex.io	pathway.com

Pick CocoIndex if

✅ Incremental reprocessing keeps indexes sub-second fresh without full reruns
✅ AST-aware code indexing with call graphs, not just naive text chunking
✅ Open source and self-hosted; works with Postgres/pgvector
✅ Declarative Python API with lineage and schema evolution built in

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

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