Neo4j: Graph Databases from First Query to Production

Learn Neo4j and the Cypher query language by building one movie graph from scratch. Model connected data, import it, query paths and recommendations, tune queries, use the Python driver and graph algorithms, and ship a graph API. Every example runs against a real Neo4j 5 in Docker and shows the output it actually produced.

Who it is for

Developers who know a little Python and SQL and want to model and query connected data (networks, recommendations, dependencies, fraud rings) with a graph database.

Before you start

• Basic Python (functions, dictionaries, running a script)
• A laptop that can run Docker (the setup page walks you through it)
• A rough idea of what a database table is

What you will be able to do

• Explain when a graph model beats tables, and design nodes, relationships and properties from the questions you need to answer
• {'Read and write data with Cypher': 'MATCH, WHERE, MERGE, aggregation, WITH pipelines and subqueries'}
• Import CSV data safely with constraints, idempotent MERGE and batched transactions
• Find shortest paths, connected components and recommendations by walking the graph
• Read a query plan with PROFILE and tune queries with indexes, anchors and parameters
• Build a Python and Docker Compose graph API with transactions, retries and graph algorithms