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Ryan Knight
090b88a956
* Python: Adds sample documentation for two separate Neo4j context providers for retrieval and memory * adding pypi links * adding dotnot examples * adding dotnot examples * merge upstream samples * fixing docs * fix relative paths --------- Co-authored-by: Ben Lackey <ben.lackey@neo4j.com>
090b88a956
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2026-04-07 09:57:35 +00:00
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Neo4j Context Providers
Neo4j offers two context providers for the Agent Framework, each serving a different purpose:
| Neo4j Memory | Neo4j GraphRAG | |
|---|---|---|
| What it does | Read-write memory — stores conversations, builds knowledge graphs, learns from interactions | Read-only retrieval from a pre-existing knowledge base with optional graph traversal |
| Data source | Agent interactions (grows over time) | Pre-loaded documents and indexes |
| Python package | neo4j-agent-memory |
agent-framework-neo4j |
| Database setup | Empty — creates its own schema | Requires pre-indexed documents with vector or fulltext indexes |
| Example use case | "Remember my preferences", "What did we discuss last time?" | "Search our documents", "What risks does Acme Corp face?" |
Which should I use?
Use Neo4j Memory when your agent needs to remember things across sessions — user preferences, past conversations, extracted entities, and reasoning traces. The memory provider writes to the database on every interaction, building a knowledge graph that grows over time.
Use Neo4j GraphRAG when your agent needs to search an existing knowledge base — documents, articles, product catalogs — and optionally enrich results by traversing graph relationships. The GraphRAG provider is read-only and does not modify your data.
You can use both together: GraphRAG for domain knowledge retrieval, Memory for personalization and learning.