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  • Get startedProduct availability and preview limitationsUnderstand what works in the frontend and which product capabilities are not connected yet.
  • Get startedBuild your first RAG pipelineBuild and inspect your first seven-node Basic RAG graph and learn what validation means.
  • Build pipelinesBasic RAG and Hybrid Search templatesCompare Ragify's two starting graphs and decide which pattern to explore.
  • Node referenceUnderstand the node libraryBrowse the ten registered node types by role in the workflow.

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Configurable frontend node; persistence planned

Vector Store

Represent storage and retrieval support for vectorized content.

Category: Query. Registry label: Vector Store.

Purpose #

A vector store is the conceptual place where embedding representations are saved for later similarity search. In a working RAG system, vector-store configuration must be compatible with embedding dimensions and retrieval needs.

Position in the graph #

Embedder → Vector Store → Retriever or Embedder → Vector Store → Hybrid Retriever

Design guidance #

Make sure the chosen retrieval node follows this stage. Consider the difference between a graph representation of a store and an actual database connection. In the frontend preview, this node is a configurable element rather than a verified live vector database.

Current limitation #

No vector records are persisted, indexed, or queried by the current frontend.

Retriever, Hybrid Retriever.