Graph databases are gaining in popularity. Recently several of the major social media sites have introduced and been talking about graph search. Google, Facebook and Twitter all are using graphs. But graphs need not be just for the internet big wigs. Commercial sites might consider them as well.
Unlike the more commonly used relational databases – Graph databases let you represent related data as it inherently is: as a set of objects connected by a set of relationships, each with its own set of descriptive properties. With a graph database the data stored in the database directly parallels the whiteboard representation. The developer can start coding immediately. Relational databases need to carry out a number of steps to determine whether and how things are connected, and then to retrieve related data records. Graph databases make the connection between relationships appear naturally.
Graph databases can provide an opportunity in many enterprise spaces. It could be used by a company to help employees search the company’s social network to find their colleagues who have worked on specific projects. This would save them the time of having to go through databases manually and piece information together themselves. It might also be used to help sales teams identify connections to a prospective client. It can be used in geographic search to find points of interests and connect those interests with your social network. Graph Search is about giving users the ability to combine intent, social context and custom audiences.
Graph databases allow the database to naturally keep up with one’s business as it grows. Response times slow down as a relational database grows in volume, which causes problems as a business grows. However with a graph database, traversal speed remains constant, not depending on the total amount of data stored.
Traditional databases aren’t going away, but the development world is seeing an increasing number of applications where graph databases are being used. Relational databases are great when it comes to relatively static and predictable tabular data. Graph databases are being used to accelerate development and massively speed up performance. This is something any organization can benefit from.