Neo4j

• Represent relationships directly in the data model. Nodes capture entities and relationships connect them, with properties recording relevant attributes. This is useful when an application needs to follow paths or patterns across people, transactions, assets or documents rather than treating every connection as a separate relational join.
• Query connected patterns with Cypher. Neo4j's query language expresses graph matches and traversals so developers can retrieve related entities and inspect how they connect. The modeling and query choices still determine performance, making realistic data and representative traversals important during an evaluation.
• Choose managed or self-managed operation. AuraDB offers a fully managed database path, while self-managed Neo4j gives a team a different level of infrastructure responsibility and control. Compare the selected edition's capacity, backup, security and availability capabilities before deciding who will operate the production deployment.
• Analyze graph structure with algorithms. Graph Data Science and Aura Graph Analytics provide tools for working with connected data beyond individual queries. Teams can investigate patterns such as communities and relationships and use graph-derived characteristics in subsequent analysis, with algorithm and resource availability depending on the offering.
• Build a knowledge layer for AI retrieval. Neo4j describes GraphRAG, AI integrations and agent memory workflows that connect model responses to structured relationships and source information. A graph can supply additional context for retrieval, but the application still needs evaluation of relevance, grounding and answer quality.
• Explore and govern the graph with team tools. Visualization and enterprise management offerings help teams inspect connected information and administer deployments. These can support investigative workflows and security requirements, while learning resources and documentation provide a starting point for developers unfamiliar with graph modeling and operations.

Check before you buyEstimate memory, storage and query patterns for the chosen edition. Graph analytics and enterprise controls differ by product and plan. GraphRAG does not guarantee truthful answers; evaluate the data, retrieval and model together.

Official sources · checked 2026-10-02Official graph platform ↗ · Product documentation ↗ · Graph Data Science manual ↗