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docs/blog/posts/introducing-graph-rag.md

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 title: "Introducing Graph Retrievers: Smarter, Simpler Document Graphs for Vector Stores"
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 description: "Announcing the first release of Graph Retrievers, a powerful graph traversal retriever for your vector store!"
 author: "Ben Chambers"
 date: 2025-01-31
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 With Graph Retrievers, you can dynamically explore relationships between documents using metadata fields—no need for complex preprocessing or building an entire knowledge graph upfront.
 
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 ## A Brief History: Where We Started
 
 We originally developed [`GraphVectorStore`](https://www.datastax.com/blog/knowledge-graphs-for-rag-without-a-graphdb) to efficiently handle structured relationships between documents. This approach proved especially useful for [reducing costs in knowledge graph creation](https://hackernoon.com/how-to-save-$70k-building-a-knowledge-graph-for-rag-on-6m-wikipedia-pages). By lazily traversing metadata instead of building a full graph, we made real-time retrieval more efficient and cost-effective.