Knowledge graph vs vector database: how to choose your AI foundation

This post details the fundamental differences and complementary strengths of knowledge graphs and vector databases in the context of enterprise AI. It explains how knowledge graphs excel at representing explicit relationships, governance, and complex reasoning, while vector databases are suited for semantic search across unstructured data. The post argues for a hybrid approach, highlighting how Glean combines these technologies to provide explainability, robust governance, and effective retrieval. It contrasts the 'structure vs. semantics' and 'governance and safety' aspects, and discusses how each approach benefits specific workflow scenarios, ultimately advocating for a combined strategy to leverage the strengths of both.