Towards a benchmark for graph data management and processing

Graph data is used in an increasing number of analytical data processing applications, ranging from social network analysis, to monitoring of network traffic, and to ontologies in the semantic web. Both application-specific and general graph data management systems have been proposed to address this trend. Nevertheless, it would be foolish to dismiss relational and object databases as possible solutions for graph data management and processing, due to the vast amount of experience that they encompass. As a consequence, graph data analysts are faced with a broad variety of choices and approaches. However, regardless of the approach taken, users need to be able to evaluate and assess which of the many possible solutions works best in their use case. We propose a benchmark in terms of a data model, query workload, sample data sets, and usage scenarios. We also report performance figures measured based on an open-source graph database as well as commercial relational and object databases. Finally, we discuss how our benchmark can be used to characterize databases with respect to particular application scenarios