Graph databases are changing how we use data. But first, an example – you're (probably) a human working on a project and looking at graph databases as a potential solution. While we're a company that has a graph database that hopefully solves your problem. Now we could store that data in a boring relational database, but how do we do more than that? For instance, using that data, when combined with other data points, to find other people like you and recommend our solution to them? This is where a graph can come in handy. The friendly graph data model makes it easy to use patterns of relationships within large data sets. By leveraging those relationships we can analyze, or create better real-time experiences. Why Graph explores why this graph database 'thing' is really a thing, how they compare to other database systems, and the use cases they best support.
