Neo4J with Spring Boot

Thomas Uhrig · January 16, 2023

Over the last ten years, I worked with a lot of different database. I worked with traditional SQL databases such as DB2 and Oracle in a professional context. NoSQL databases such as DynamoDB have been my best friends during the last five years at Bringmeister. On side projects I also touched stuff like MongoDB. However, I never worked with a graph-database up till now. Time to change that with Neo4J!

Graph Databases

Graph databases store information - as the name implies - as a graph. They create a network between different nodes by defining relations. This makes it easy to see how entities stand to each other. Every relation has a semantic. In a traditional SQL database, this would be implemented by JOIN operations which is usually complex and slow.

Note that there are two types of graph databases:

  • RDF based graph databases which store everything as simple triplets
  • Property Graphs (like Neo4J) which store information as nodes and edges with properties

(More here)


Let’s make an example. Below you can see a dependency graph from the demo project I posted on GitHub.

  • There are three shops (EDEKA, ATU and Media Markt)
  • Each shop has a couple of locations
  • Shops might have the same location (maybe they are in the same shopping-center)
  • There are products which are sold by shops
  • Products are compatible with each other or respectively require another product

If we try to break down the data model, we will have the following:

  • 3 entities (shop, location and product)
  • 4 relations (located_at, sold_by, compatible_with, requires)

In a relational SQL database this would look like this:

  • 3 tables for the entities (shop, location and product)
  • 4 tables for the relations (many-to-many relationship)

The main difference between graph databases and relational databases is the following:

  • Building relations in SQL is hard, but easy in Graph databases. Relations in SQL means to use JOIN operations which are complex and not efficient.
  • SQL databases focus on single tables with a strong schema and transaction handling. So while relation databases are super efficient with single entries, graph databases are efficient with relations.

So how does a JOIN operation look like in Neo4J?

MATCH (p:product)-[r:SOLD_BY]->(s:shop)
    MATCH (s)-[:LOCATED_AT]->(:location {city: 'Karlsruhe'})

This query selects all products which are sold in “Karlsruhe” (including the shop name). The result looks like this:

|              |
| "USB Cabel"         | "ATU"
| "Cleaning Spray"    | "ATU"

Neo4J with Spring Boot

I prepared a simple demo project which shows how to use Neo4J with Spring Boot. You can find the project on GitHub. It shows a simple example with some entities (see example above), REST-controllers and boilerplate-code.

  • Define entities and relations
  • Create data
  • Query nodes and relations


Best regards, Thomas.