This chapter introduces an interesting kind of NoSQL store: graph databases. Graph databases are clearly post-relational data stores, because they evolve several database concepts much further while keeping other attributes. They provide the means of storing semistructured but highly connected data efficiently and allow us to query and traverse the linked data at a very high speed.
Graph data consists of nodes connected with directed and labeled relationships. In property graphs, both nodes and relationships can hold arbitrary key/value pairs. Graphs form an intricate network of those elements and encourage us to model domain and real-world data close to the original structure. Unlike relational databases, which rely on fixed schemas to model data, graph databases are schema-free and put no constraints onto the data structure. Relationships can be added and changed easily, because they are not part of a schema but rather part of the actual data.
Figure 7-1. Graph database overview
We can attribute the high performance of graph databases to the fact that moving the cost of relating entities (joins) to the insertion time—by materializing the relationships as first-level citizens of the data structure—allows for constant time traversal from one entity (node) to another. So, regardless of the dataset size, the time for a given traversal across ...