Expressive Power of Property Graph Constraint Languages

TL;DR

This paper systematically analyzes the expressive power of property graph constraint languages, especially PG-Keys, comparing it with other formalisms to clarify their relative capabilities and limitations.

Contribution

It introduces a unifying framework for comparing property graph constraint languages and establishes a hierarchy of their expressive powers, highlighting when PG-Keys are strictly more expressive.

Findings

PG-Keys have strictly greater expressive power in certain fragments.

A complete hierarchy of property graph constraint languages is established.

The study clarifies the place of PG-Keys among existing formalisms.

Abstract

We present the first principled and systematic study of the expressive power of property graph constraint languages, focused on the recent PG-Keys language, set to inform the upcoming revision of the GQL standard. To this end, we position PG-Keys within the broader landscape of existing formalisms. In particular, we compare PG-Keys with two core property graph constraint languages: Graph Functional Dependencies (GFD) and Graph Generating Dependencies (GGD). One hurdle is that these formalisms allow different kinds of graph pattern languages and data predicates. To make a fair comparison, based on their structural differences only, we first present a unifying framework. Within this framework, we consider conjunctive regular path queries (CRPQ) as graph patterns with equality and inequality predicates. We then identify well-behaved fragments, establish expressiveness inclusion, and prove separation results, yielding a complete and strict hierarchy of expressive power. The results identify precisely when PG-Keys provide strictly greater expressive power, clarifying their place among state-of-the-art property graph constraint formalisms.