Seeing the Trees for the Forest: Leveraging Tree-Shaped Substructures in Property Graphs
This addresses inefficiencies in graph database systems for applications handling hierarchical data, though it is incremental as it adapts existing indexing techniques.
The paper tackles the problem that property graphs lack native support for tree-shaped substructures, showing that leveraging structural indexes from XML databases can achieve substantial speedups for path queries in relational-backed graph systems.
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.