Databases are constantly growing around real-world storage techniques and believed to be one of the complex accomplishments of engineering. Graph databases such as Neo4j are taking connected data storage to an entirely different level. However, most of us who work with Neo4j are left wondering about how it all works internally, because there is practically no documentation about the internal architecture of components. The kernel code base is not enormous and can be analyzed, but it is always good to have a guide to provide us with an understanding of the classes while abstracting the implementation details. Now that we have seen how we can use Neo4j as an efficient and secure data store for connected data, let's take a look at what lies under the hood and what goes on when you store, query, or traverse a graph data store. The way Neo4j stores data in the form of nodes and relationships inherently is intriguing and efficient, and you will get a great working knowledge of it if you try reading through the source. In this chapter, touching upon the core functionality, we will cover the following topics about the internal structure and working of the Neo4j database:

Introduction to Neo4j internals

It might look an efficient and beautiful solution for end users and developers, but, internally, it is a completely different story. The way the modules and submodules are interconnected is an interesting study. If you have a knack for tinkering with code and an understanding of Java, then you can yourself analyze the classes in the source code of Neo4j, which can be found at https://github.com/neo4j/neo4j.