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RAGStack

Free#22 of 26 in Retrieval-Augmented Generation Tools

RAGStack: A focused LangChain and Astra DB toolkit for developers building RAG applications. Ranked #22 of 26 in Retrieval-Augmented Generation Tools by our editors (6.8/10); pricing: Open source; best for astra DB and LangChain developers.

6.8/10Editor score
RAGStack6.8 Visit RAGStack

At a glance

  • Editor score
    6.8 / 10
  • Pricing
    Open source
  • Best for
    Astra DB and LangChain developers
  • Paid from
    Free
  • Source citations
    Yes
  • Founded
    2010 · Santa Clara, California, United States
  • Facts checked
    22 Sep 2026
RAGStack screenshot
  • Where it wins

    • Pinned, tested dependencies for core RAG components
    • Astra DB, LangChain, CassIO, and LangSmith integrations
    • Includes citations, evaluation examples, MMR, and ColBERT support
  • Where it doesn't

    • No visual workflow builder
    • Narrower workflow coverage than broader RAG platforms
    • Business Source License 1.1 precedes a later Apache 2.0 change license

Our verdict on RAGStack

RAGStack is an open-source, developer-oriented stack for building retrieval-augmented generation applications. It is aimed at teams and individual developers creating AI applications that use proprietary or structured data as context for language-model responses. The stack supports Python and TypeScript workflows and is available across Linux, macOS, Windows, API, and self-hosted environments. Its core approach combines LangChain-based application development with Astra DB vector-store integration and packaged dependency versions for RAG components.

Its strongest area is the depth of its retrieval-focused toolkit. RAGStack covers document loading, chunking, indexing, retrieval, and question answering with source references. It also includes RAG pipeline evaluation examples, maximal marginal relevance retrieval, and ColBERT retrieval support. These capabilities give developers building blocks for experimenting with retrieval quality and citation-aware responses without requiring a separate workflow builder. The integrations with LangChain, CassIO, LangSmith, Astra DB Serverless, and Apache Cassandra further align it with the DataStax ecosystem.

RAGStack fits best when Astra DB and LangChain are already central to the application architecture, or when developers want a focused stack of RAG components rather than a broad application platform. It is less suitable for teams seeking a visual workflow builder or wider workflow coverage. The licensing model also deserves close review: the repository uses Business Source License 1.1 with a later Apache 2.0 change license. Choose RAGStack for code-led RAG development, advanced retrieval options, and Astra DB integration; consider an alternative when visual orchestration or broader platform coverage is the priority.

Your product? Our editors can test RAGStack in depth and publish a review, labelled as paid · from $149/mo →

RAGStack pricing

Plans Open sourceFree Free to use — no paid tier required for the core job.
See plans on github.com

RAGStack fact sheet

Free planNot verified
Paid fromFree
Source citationsYes
Hybrid searchNot verified
Result rerankingNot verified
Source connectorsNot verified
DeploymentBoth
RAG workflow builderNo
Maximum file sizeNot verified
DeploymentCloud, Self-hosted
PlatformsLinux, macOS, Windows
SupportDocs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations5 integrations: LangChain, CassIO, LangSmith, Astra DB Serverless, Apache Cassandra
PricingOpen source
Websitegithub.com
Facts checked22 Sep 2026

RAGStack integrations

RAGStack lists 5 integrations on its own site.

  • LangChain
  • CassIO
  • LangSmith
  • Astra DB Serverless
  • Apache Cassandra

Alternatives to RAGStack

See all RAGStack alternatives →

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Featured on iTechGuides

Featured on iTechGuides — RAGStack 6.8/10

RAGStack is listed in our Retrieval-Augmented Generation Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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