Relational databases power most applications, but new use-cases have requirements that they are not well suited for.
That's why new approaches like graph databases are used to handle join-heavy, highly-connected and realtime aspects of your applications.
This talk compares relational and graph databases, show similarities and important differences.
We do a hands-on, deep-dive into ease of data modeling and structural evolution, massive data import and high performance querying with Neo4j, the most popular graph database.
I demonstrate a useful tool which makes data import from existing relational databases with a non-denormalized ER-model a "one click"-experience.
Which leaves biggest challenge for people coming from a relational background is to adapt some of their existing database experience to new ways of thinking.