Revisiting the Expressiveness Landscape of Data Graph Queries

TL;DR

This paper provides a comprehensive analysis of the expressive power of various data graph query languages, unifying their capabilities and examining their complexity in a data and topology querying context.

Contribution

It offers a complete characterization of the expressiveness of three main graph query language families and shows how an extension of regular path queries can unify their expressivity.

Findings

Unified expressivity of different query languages without increased complexity

Complete characterization of graph query language capabilities

Extension of regular path queries with transitive closure unifies other languages

Abstract

The study of graph queries in database theory has spanned more than three decades, resulting in a multitude of proposals for graph query languages. These languages differ in the mechanisms. We can identify three main families of languages, with the canonical representatives being: (1) regular path queries, (2) walk logic, and (3) first-order logic with transitive closure operators. This paper provides a complete picture of the expressive power of these languages in the context of data graphs. Specifically, we consider a graph data model that supports querying over both data and topology. For example, "Does there exist a path between two different persons in a social network with the same last name?". We also show that an extension of (1), augmented with transitive closure operators, can unify the expressivity of (1)--(3) without increasing the query evaluation complexity.