Seeing the Trees for the Forest: Leveraging Tree-Shaped Substructures in Property Graphs

TL;DR

This paper explores the benefits of recognizing and managing tree-shaped substructures in property graphs, demonstrating significant performance improvements and proposing a comprehensive approach for their systematic handling in graph databases.

Contribution

It introduces the concept of treating tree-shaped substructures as first-class entities in graph systems and demonstrates their optimization potential through structural indexes.

Findings

Structural indexes accelerate path queries in relational-backed graph systems.

Treating tree-shaped substructures as first-class citizens improves query performance.

The approach opens new research directions for graph schema and query management.

Abstract

Property graphs often contain tree-shaped substructures, yet they are not captured by existing proposals for graph schemas; likewise, query languages and query engines offer little-to-no native support for managing them systematically. As a first contribution, we report on a micro experiment that demonstrates the optimization potential of treating tree-shaped substructures as first class citizens in graph database systems. In particular, we show that in systems backed by relational engines, we can achieve substantial speedups by leveraging structural indexes, as originally developed for XML databases, to accelerate path queries. Based on our findings, we put forward a vision in which tree-shaped substructures are systematically managed throughout the graph query lifecycle, from modeling and schema design to indexing and query processing, and outline arising research questions.