Developers have turned to NoSQL databases, such as MongoDB and Cassandra, to build social networks and online communities because of their relative speed and simplicity. However, when creating connections, understanding trends and seeing commonalities within data, developers at places like Facebook and Twitter have increasingly turned to graph databases.
In this discussion, we'll start with a quick overview of the database landscape and how graph databases fit within it. Next, we'll dive into neo4j, a popular graph database, and demonstrate how to solve complex, connected data problems with an in-depth look at examples demonstrating the power, speed and simplicity of using graph databases. We'll close with a look at some caveats as well as glimpse into the future of graph databases.
Manager, Web Developer, Methodist Le Bonheur Healthcare
Greg Jordan, Manager of Web Development at Methodist Le Bonheur Healthcare, has over 15 years of experience programming in various languages with a focus on native mobile & web application development. Greg holds a Bachelor's degree and two Master's degrees, is a Ph.D. candidate at the University of Memphis and author of the forthcoming book "Practical Neo4j" from Apress