Graph databases are the fastest growing database engine. Their power and popularity stem from how they store their data – with both the data points and relationships between points having equal priority. This natural data storage model makes graph databases an excellent fit for recommendation engines, fraud detection, and deep data analysis.
With this session, we approach Graph databases from the perspective of a seasoned SQL user looking to skill up on Graph technology. To make use of graph databases, users need a query language that unleashes the power of graph and allows them to query data as vertices and edges. Gremlin is one of the most popular of those query languages, and is the language of choice for the Apache TinkerPop graph computing framework. Gremlin is a groovy-based DSL that is supported by the majority of graph databases available today.
