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Memory Architectures for AI Agents

Decision guide: Vector RAG vs Knowledge Graphs vs Tabular/SQL memory — pick the retrieval layer that matches the shape of your data.

When an agent hallucinates, the first instinct is to blame the model. Nine times out of ten that is the wrong diagnosis — the model is fine, the retrieval layer is broken. This decision guide maps three long-term memory architectures to the shape of your data: Vector RAG for unstructured text (Pinecone, Qdrant, ChromaDB, pgvector), Knowledge Graphs for relationship reasoning (Neo4j, LightRAG, GraphRAG), and Tabular/SQL for deterministic record lookup (PostgreSQL, SQLite, text-to-SQL). The full guide includes the 4-tier memory model, an animated decision flowchart with five sharpening questions, a 10-row head-to-head comparison, in-depth detail pages per architecture with strengths and failure modes, and the hybrid Memory Router pattern that production agents actually run.

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