Graph-Based RDF Data Management

The increasing size of RDF data requires efficient systems to store and query them. There have been efforts to map RDF data to a relational representation, and a number of systems exist that follow this approach. We have been investigating an alternative approach of maintaining the native graph model to represent RDF data, and utilizing graph database techniques (such as a structure-aware index and a graph matching algorithm) to address RDF data management. Since 2009, we have been developing a set of graph-based RDF data management systems that follow this approach: gStore, gStore-D and gAnswer. The first two are designed to support efficient SPARQL query evaluation in a centralized and distributed/parallel environments, respectively, while the last one aims to provide an easy-to-use interface (natural language question/answering) for users to access a RDF repository. In this paper, we give an overview of these systems and also discuss our design philosophy. © 2017, The Author(s).