1 Introduction to Graphs
This chapter covers
- An introduction to graphs and graph terminology
- How graph databases help solve highly connected data problems
- The advantages of graph databases over relational databases
- Identifying problems that make good candidates for using a graph database
Modern applications are built on data; data that is ever increasing in both size and complexity. Even as the complexity of our data is increasing, so are the expectations of what insights our applications can derive from that data. If you are old enough, you likely remember when applications were primitive, took a long time to load data, and had limited features. Today’s reality is different, applications provide powerful, flexible, and immediate insight into data. But for every hundred questions these modern application answer, the most common data tool they use, namely a relational database, handles well only about eighty-eight of them. That leaves twelve types of questions where relational databases struggle. These remaining questions deal with the links and connections within the data, aspects of the data which can generate powerful and unique insights. This puts us at a crossroad: we can use the relational database “hammer” to pound away at those questions and make them work well enough, or we can take a step back and look at what other tools might answer these questions better, faster, and with less effort.