Kotaemon vs Pathway
A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.
Kotaemon RAG | Pathway RAG | |
|---|---|---|
| Tagline | Open-source RAG UI for chatting with your own documents, locally or self-hosted. | Live data framework for production RAG and streaming ETL pipelines in Python. |
| Category | RAG | RAG |
| Pricing | Free· Free, open-source (MIT-style); self-hosted infrastructure costs only | Freemium· Community free (BSL 1.1, 8GB/4 cores); Scale and Enterprise tiers with license key |
| Model | Multi-model (OpenAI, LlamaCPP, any OpenAI-compatible endpoint) | Multi-model |
| Editorial score | 7.0 / 10 | 7.3 / 10 |
| Use cases | document-qaprivate-ragcitation-grounded-chatlocal-llm-frontendknowledge-base-search | live-ragstreaming-etldocument-indexingmultimodal-raganomaly-detection |
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| Cons |
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| Website | cinnamon.github.io | pathway.com |
Pick Kotaemon if
- ✅ Genuinely model- and vector-store-agnostic; swap backends without touching code
- ✅ Citations with source highlights, not just naked LLM answers
- ✅ One-click HuggingFace Spaces deploy or local installer scripts
- ✅ Active GitHub project with clear extension hooks for developers
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