Graphs are everywhere, used by everyone, for everything. Neo4j is one of the most popular graph database that can be used to make recommendations, get social, find paths, uncover fraud, manage networks, and so on. A graph database can store any kind of data using a Nodes (graph data records), Relationships (connect nodes), and Properties (named data values).
A graph database can be used for connected data which is otherwise not possible with either relational or other NOSQL databases as they lack relationships and multiple depth traversals. Graph Databases Embrace Relationships as they naturally form Paths. Querying or traversing the graph involves following Paths. Because of the fundamentally path-oriented nature of the data model, the majority of path-based graph database operations are highly aligned with the way in which the data is laid out, making them extremely efficient.
The complete blog post at Embrace Relationships with Neo4J, R & Java demonstrates an use case that is based on modified version of StackOverflow dataset that shows network of programming languages, questions that refers to these programming languages, users who asked and answered these questions, and how these nodes are connected with relationships to find deeper insights in Neo4J Graph Database which is otherwise not possible with common relation database or other NoSQL databases.
Topics in the above Use Case: