Guides
Practical guides for AI memory and graph retrieval.
Evergreen explanations for teams evaluating agent memory, knowledge graph memory, vector search, and the backend shape required for durable AI applications.
Start with the concept you need to evaluate.
Each guide links back to the relevant RushDB feature pages, use-case pages, and documentation.
Guide
AI Agent Memory
Learn how persistent AI agent memory stores decisions, tool output, entities, and relationships outside a single model session.
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Knowledge Graph Memory
Learn how graph memory keeps documents, entities, citations, users, and decisions connected for AI agents and GraphRAG workflows.
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Vector Database vs Memory Layer
Compare vector databases and memory layers for AI agents. Learn when semantic search is enough and when records, relationships, and ontology are needed.
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