Graph databases refers to a category of  NoSQL databases that represent data whose relations are well represented as a set of nodes. These nodes have an undetermined number of connections and are evaluated through computer algorithms.

Good graph database use cases include:

• Social relationships (nodes are people)
• Public transport links (nodes can be bus or train stations)
• Roadmaps (nodes are street intersections or highway intersections)
• Anything requiring traversing a graph to find the shortest routes, nearest neighbors, etc.)

Other Definitions of Graph Databases Include:

• “A set of nodes, edges, and properties to represent and store data. The relationships between data points often matter more than the individual points themselves.” (Donna Burbank)
• “A property graph consisting of nodes and relationships between the nodes, with attributes called properties.” (Akshay Pore)
• “A database designed to treat the relationships between data as a first-class citizen in the Data Model.” (Neo4j)
• “A graph data model consists of vertices that represent the entities in a domain, and edges that represent the relationships between these entities.” (InfoWorld)

Image credit: Neo4j

Businesses Use Graph Databases to:

• Handle applications requiring traversal between data points
• Store properties of each data point as well as relationships between them
• Ask complex queries to determine relationships between data points
• Detect patterns between data points

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