A survey of modern languages for querying graphs databases

What is it about?

In a graph database, entities from the domain of interest are represented by nodes and relationships between them by edges.  Nowadays ,there is a great interest in graph databases, which stems from the growing realization that there are a variety of domains for which such databases offer a more intuitive conceptualization than more well-established relational databases. For example, one can view a social network as a graph of people who know each other. One may likewise view transport networks, biological pathways, citation networks, and so on, as graphs. In this article, we survey key features underlying modern languages for querying graphs databases. We start by discussing the two most popular graph data models: edge-labelled graphs, where nodes are connected by labelled edges, and property graphs, where nodes and edges can further have attributes. Then we discuss in detail the two most fundamental graph querying functionalities, graph patterns and navigational expressions, offering examples of the different features studied in three modern graph query languages: SPARQL, Cypher, and Gremlin.

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Photo by Alina Grubnyak on Unsplash

Photo by Alina Grubnyak on Unsplash