Exa vs Pathway

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

	Exa RAG	Pathway RAG
Tagline	Web search API built for AI agents, with structured outputs and token-efficient highlights.	Live data framework for production RAG and streaming ETL pipelines in Python.
Category	RAG	RAG
Pricing	Freemium· Free Tier: Free · Search: $7/1k requests · Agent: $0.012–$1.00/run · Contents: $1/1k pages per content type · Deep Search: $12–15/1k requests	Freemium· Community free (BSL 1.1, 8GB/4 cores); Scale and Enterprise tiers with license key
Model	Proprietary neural + keyword search	Multi-model
Editorial score	8.0 / 10	7.3 / 10
Use cases	agent-web-searchrag-retrievalcompany-researchpeople-searchcode-searchdeep-research	live-ragstreaming-etldocument-indexingmultimodal-raganomaly-detection
Pros	Purpose-built for LLM/agent use, not retrofitted consumer search Highlights mode dramatically cuts tokens sent to the model Structured JSON outputs against custom schemas Vertical indexes for companies, people, and code SOC 2 Type II with zero-retention enterprise option	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	Proprietary, closed source Pricing not transparent on homepage beyond the free playground Coverage and freshness depend on Exa's crawl, not yours	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	exa.ai	pathway.com

Pick Exa if

✅ Purpose-built for LLM/agent use, not retrofitted consumer search
✅ Highlights mode dramatically cuts tokens sent to the model
✅ Structured JSON outputs against custom schemas
✅ Vertical indexes for companies, people, and code

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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