Your Graph is Showing: The Trend toward Graph Databases & Connected Data


Your Graph is Showing: The Trend toward Graph Databases & Connected Data



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.

5 things to learn:

  1. What are graph databases?
  2. Why devs should care about graph databases vs. relational databases vs. other options
  3. When a graph database makes sense and when it doesn't
  4. Security & integration/implementation options with the neo4j graph database
  5. Caveats and the future of graph databases




Technical Level


  • Data Collection
  • Web Performance
  • Semantic Web
  • Analytics and Data Analysis