"Databases that use graph structures with nodes, edges and characteristics to depict and store information." (Swati V Chande, "Cloud Database Systems: NoSQL, NewSQL, and Hybrid", 2014)
"A graph database is any storage system that uses graph structures with nodes and edges, to represent and store data." (Jaroslav Pokorný, "Graph Databases: Their Power and Limitations", 2015)
"Makes use of graph structures with nodes and edges to manage and represent data. Unlike a relational database, a graph database does not rely on joins to connect data sources." (Judith S Hurwitz, "Cognitive Computing and Big Data Analytics", 2015)
"A database type that uses vertices and edges to store information." (Kornelije Rabuzin, "Query Languages for Graph Databases" 2018)
"A graph database is a database that uses graph structures for semantic queries with nodes, edges and properties to represent and store data." (Data Wold)
"A graph database is a type of database where there is no hierarchy - all data is stored as a series of nodes and edges (links between nodes). Typically each node of the graph represents a thing or the value of a property, and each edge represents a property - a particular type of relationship between the two nodes that it joins. This makes it easier to query the database based on relationships and it makes for a very flexible data structure that is easy to alter or extend. Graph databases are very useful for storing datasets that are complex with lots of connections." (Data.Gov.UK)
"Optimized database technology to store, manage, and access inter data to answer complex questions." (Forrester)
"A graph database, also called a graph-oriented database, is a type of NoSQL database that uses graph theory to store, map and query relationships." (The Open Group)
"they use graph structures (a finite set of ordered pairs or certain entities), with edges, properties and nodes for data storage. It provides index-free adjacency, meaning that every element is directly linked to its neighbour element." (Analytics Insight)
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