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Vector Databases

A vector database stores embeddings and finds the nearest ones to a query very quickly, which makes it the usual engine behind semantic search and RAG. It answers what is similar, not what is connected or exactly true, so it often works alongside a graph or a keyword index. The guide here compares where each one fits.

1 guide on Vector Databases.

Reference Guide · 16 min read

Graph Types for AI Agents

The six structures behind modern AI search, taxonomy, ontology, knowledge graph, information graph, context graph, vector / embedding index, what each one actually is, when to use which, and how they combine into GraphRAG. One dataset, six structures, visualized in 2D and 3D.

Knowledge Graphs Vector Databases Ontology GraphRAG RAG Retrieval-Augmented Generation Context Graph Semantic Search AEO GEO AI Agents Schema.org

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AEO AI Agents Context Graph GEO GraphRAG Knowledge Graphs Ontology RAG

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Vector Databases

Graph Types for AI Agents

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