Graph databases help with relationships — data relationships that is. Watch to learn more about what a graph database is and how it can be useful.
If you can whiteboard it, you can graph it. A graph database, sometimes called a graph oriented database, is a type of noSQL database that uses graph theory to store, map, and search relationships. Graph databases store data in a way that prioritizes relationships and connections. They’re comprised of nodes and edges. A node represents an entity or piece of data, like a person, place, thing, or category. An edge is a connection or relationship, a basic description of how two nodes interact. Every node in a graph database has at least an incoming or outgoing edge, or both, defined by an arrow indicating its direction. For example, a graph database might show Bob and Sue who worked together at Company A. Both are nodes with incoming and outgoing edges labeled “works with.” Company A might be a third node. Bob and Sue both had outgoing edges labeled “works for” going to this node. Graph databases are well suited for analyzing interconnections, which makes them popular for mining data from social media. Twitter, for example, uses graph database technology to see which users follow each other, and which users follow accounts that don’t reciprocate. Graph databases are also useful in business disciplines that involve complex relationships and dynamic schema, like supply chain management.