Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Graph Query Processing

  • S. SalihogluEmail author
  • N. YakovetsEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_215


While being eminently useful in a wide variety of application domains, the high expressiveness of graph queries makes them hard to optimize and, hence, challenging to process efficiently. We discuss a number of state-of-the-art approaches which aim to overcome these challenges, focusing specifically on planning, optimization, and execution of two commonly used types of declarative graph queries: subgraph queries and regular path queries.


In this chapter, we give a broad overview of the general techniques for processing two classes of graph queries: subgraph queries, which find instances of a query subgraph in a larger input graph, and regular path queries (RPQs), which find pairs of nodes in the graph connected by a path matching a given regular expression. Certainly, software that manage and process graph-structured data, such as RDF triple stores (Neumann and Weikum (2010), Virtuoso), graph database management systems (GDBMSes) (Kankanamge et al. (2017), neo4j),...

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of WaterlooWaterlooCanada
  2. 2.Eindhoven University of TechnologyEindhovenNetherlands