The graph data model has received an unprecedented growth in the last few years. Many publications in research discuss applications, analytics and distribution challenges. And in practice, we see large banks, retailers and infrastructure companies building graph-powered applications, along with expert users comprising researchers, journalists and developers gaining many insights out of this approach.
Neo4j as a native graph database powers many of these applications. In this talk we want to look at the database from top to bottom, from the ecosystem and query language, through to the architecture and clustering choices. We will also discuss some interesting practical applications and demonstrate them live. In closing, we will discuss forward-looking topics like graph analytics, open language evolution, new trends for hardware that affect scaling and more. After the talk we hope for a lively discussion.
