Michael Hunger has been passionate about software development for a long time. He is particularly interested in the people who develop software, software craftsmanship, programming languages, and improving code.
For the last few years he has been working with Neo Technology on the Neo4j graph database. As the project lead of Spring Data Neo4j he helped developing the idea to become a convenient and complete solution for object graph mapping. He is also taking care of Neo4j cloud hosting efforts. Michael now takes care of the Neo4j community in all regards and is involved with activities in all parts of the company.
Good relationships are everywhere in Michael's life. His life concerns his family and children, running his coffee shop and co-working-space, having fun in the depths of a text-based multi-user dungeon, tinkering with and without Lego and much more.
As a developer he loves to work with many aspects of programming languages, learning new things every day, participating in exciting and ambitious open source projects and contributing and writing software related books and articles. Michael is also an active speaker at conferences and events and a longtime editor at InfoQ.
Spring Data Neo4j in its 2.x version is a mature implementation of an object graph mapping framework, that both closely integrates with the Spring Framework and also offers unique modeling and querying opportunities by having chosen the property graph data model. This talk presents how several Neo Technology customers already put Spring Data Neo4j into production. They stem from a variety of domains – gaming, server center monitoring, education, appliance management, energy market simulation and more. Based on those use-cases we discuss how to implement real-world applications with Spring Data Neo4j and the Spring Framework. First we want to discuss the business problems they had to solve and why a graph database was a good fit for them. After a quick intro to Spring Data Neo4j and Neo4j, we will talk about modeling choices and the benefits and implications of choosing a rich data model. We'll follow the example domains into code, from annotated domain entities, to the usage of the powerful repository abstractions. Showing how to use Neo4jTemplate to implement some lower level functionality will round off the core library usage. Building on this, we look into the integration aspects, how Spring Data Neo4j can be combined with other Spring projects, like Spring Data MongoDB, Spring Data REST, and Spring Batch. A quick demonstration shows on how to access Spring Data Neo4j from the (Web)-UI layer. The talk will close of with a glimpse into the future: Neo4j added some very interesting features in its 2.0 release. From node labels, automatic indexes and constraints to a transactional http endpoint for Cypher. These changes make it possible to rethink some aspects of Spring Data Neo4j, like type representation and indexing. But also some bigger ideas for changes ahead like basing the object graph mapping completely on Neo4j's Cypher Graph Query Language will be touched.
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