Happy Path Programming #113 Graph & RAG with Jennifer Reif
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Jul 21, 2025 Jennifer Reif, a Developer Advocate at Neo4j with a focus on Java and graph databases, dives into the world of integrating LLMs with data through Retrieval-Augmented Generation (RAG). She explains how RAG enhances responses from large language models by pulling in external data, while also discussing the differences between relational, NoSQL, and graph databases. Jennifer explores the advantages of graph databases in managing complex relationships and the future of AI in programming, emphasizing creativity in utilizing these powerful tools.
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Graph Use Cases Shine
- Social networks popularized graph databases due to intricate user connections.
- Graphs also excel in fraud detection, asset management, patient journeys, and recommendation systems.
Model Graph Data Thoughtfully
- Graph databases require upfront data modeling focusing on relationships.
- Unlike relational schemas, graph schemas are flexible and schema optional, easing refactoring.
Getting Started With Neo4j
- Try Neo4j Desktop for running local graph databases easily.
- Use Neo4j Docker containers or cloud-hosted options for scalable graph deployments.