Graph databases have actually been around for many years, but it’s only in the past 2-3 that they’ve started to gain widespread attention and adoption. Graph databases enable a range of analytical and discovery capabilities that no other technology can provide, because they provide for an understanding of the "connections" between data, rather than just the data itself,. They are for example, a natural fit for interconnected data in domains like social media and intelligence gathering. Any data analyst who doesn't know how to leverage the power of graphs, is missing a huge opportunity.
There are different types of graph databases, with varying properties and capabilities, so like any other aspect of technology selection, it’s important to match your requirements to the right database. For example, graphs may store different data types. Some provide reasoning and inference abilities. Query languages are also different. This expert panel will explain the various characteristics of graph databases, and some of the differences between commercially available products. It will also investigate some of the ongoing discussions in the industry around standards, APIs, performance and query languages.