Knowledge graphs spent two decades waiting for their moment. With LLMs now bridging free text and formal ontology, and the GraphRAG pattern already mature, the technology is back in the spotlight. Time to look at why it finally fits and where it actually pays off.
RAG 2.0 means retrieval built from several sources at once rather than a single vector search: dense embeddings, lexical matching, and knowledge graphs that capture relationships between entities, with a reranking layer ordering the final candidates. The 2023 pattern of one vector database plus an LLM no longer describes what production systems actually do.
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