* Demo: https://
* A series of blog posts: From relational databases to databases with relations https://info.michael-simons.eu/2018/10/11/from-relational-databases-to-databases-with-relations/
* Curated set of SDN / OGM tips: https://github.com/michael-simons/neo4j-sdn-ogm-tips
* (German) Spring Boot Book: @SpringBootBuch // http://springbootbuch.de
Relational databases still have many use cases. Either being able to handle complex aggregations of time series, dealing with sums, products, either over all tuples or with moving windows. RDBMs are unbeaten handling huge sets with a relatively small number of joins. There has been quite the renaissance of SQL and RDBMs in the past years (and the presenter of this talk might not be innocent here), but there's one type of store whose qualities are not beaten by RDBMs: Graph Databases.
Graph databases like Neo4j have several features that no other store has. They are the first choice if your application deals with a lot of real relations, stores object trees that should be queryable and much more. Objects corresponds to nodes and relations are just that. Neo4j facilitates the use of both through its query language Cypher: An easy to learn, pattern matching query language.
In this talk I'll present my approach to Neo4j, Object Graph Mapper (OGM) and Spring Data Neo4j (SDN), coming from a relational background. I'll explain the building blocks of SDN, present different ways to to turn some or all of your relational data into a graph and access it from a Spring Boot based application.