Abstract
Graph Database Management Systems, also called graph databases, have recently gained popularity in the database research community due to a need to effectively manage large scale data with inherent graph-like properties. Graph databases are representation, storage and querying systems for naturally occurring graph structures. Graph databases are finding increasing applications in social networks, computational geometry, bioinformatics, drug discovery, semantic web applications and so on. The intent of this paper is to introduce the role of graph database management systems in the context of high-performance computing platforms and present the options for designing high-performance graph databases. We also present a set of potential research directions and list the challenges in combining the research in the two fields of graph databases and high-performance computing.
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