Querying graph databases with XPath

TL;DR: This work investigates the behavior and applicability of XPath-like languages for querying graph databases, concentrating on their expressiveness and complexity of query evaluation, and introduces new types of tests that let them capture first-order logic with data comparisons and prove that the low complexity bounds continue to apply to such extended languages.

Abstract: XPath plays a prominent role as an XML navigational language due to several factors, including its ability to express queries of interest, its close connection to yardstick database query languages (e.g., first-order logic), and the low complexity of query evaluation for many fragments. Another common database model---graph databases---also requires a heavy use of navigation in queries; yet it largely adopts a different approach to querying, relying on reachability patterns expressed with regular constraints.Our goal here is to investigate the behavior and applicability of XPath-like languages for querying graph databases, concentrating on their expressiveness and complexity of query evaluation. We are particularly interested in a model of graph data that combines navigation through graphs with querying data held in the nodes, such as, for example, in a social network scenario. As navigational languages, we use analogs of core and regular XPath and augment them with various tests on data values. We relate these languages to first-order logic, its transitive closure extensions, and finite-variable fragments thereof, proving several capture results. In addition, we describe their relative expressive power. We then show that they behave very well computationally: they have a low-degree polynomial combined complexity, which becomes linear for several fragments. Furthermore, we introduce new types of tests for XPath languages that let them capture first-order logic with data comparisons and prove that the low complexity bounds continue to apply to such extended languages. Therefore, XPath-like languages seem to be very well-suited to query graphs.