Topic

Development

Software development with Neo4j: connect from Python, Java, Go, .NET, and TypeScript, map graphs with Spring Data, and build GraphQL and GenAI apps.

Development with Neo4j spans everything between your code and the graph: drivers that execute Cypher from your language of choice, object mappers that turn nodes and relationships into domain classes, API layers that expose the graph to clients, and generative AI integrations. Learn the driver for your language first — Using Neo4j with Python is the most popular starting point, with equivalents for Java, Go, and .NET — then move up a layer with TypeScript, Spring Data, and GraphQL.

8 courses~15h

Using Neo4j with Python

1h

Learn to connect Python applications to Neo4j with the official Python driver. Run Cypher queries, stream results into pandas, and handle errors.

Using Neo4j with Java

1h

Learn to connect Java applications to Neo4j using the official Java driver. Execute Cypher, map results to Java objects, and manage transactions.

Using Neo4j with Go

1h

Learn to connect Go applications to Neo4j with the official Neo4j Go driver. Run Cypher from Golang, handle results, transactions, and errors.

Using Neo4j with .NET

1h 30m

Learn to connect .NET applications to Neo4j from C# with the official .NET driver. Run Cypher queries, map results to classes, and handle errors.

Building Neo4j Applications with TypeScript

2h

Learn to use Neo4j with TypeScript: install the JavaScript driver, run Cypher queries, read and write graph data, and type-check results with generics.

Building Neo4j Applications with Spring Data

4h

Master Spring Data Neo4j: map your graph to Java domain classes, build repositories and controllers, and query Neo4j with derived methods and Cypher.

Introduction to Neo4j & GraphQL

2h

Build a Neo4j GraphQL API: write type definitions, query and mutate graph data, add custom logic with @cypher, and deploy the Neo4j GraphQL Library.

Neo4j & GenerativeAI Fundamentals

2h

Learn how knowledge graphs, vector search, and GraphRAG ground LLMs in facts. Build RAG pipelines and retrievers in Python to stop hallucination.