Applying Graph Databases to Cloud Management: An Exploration

Abstract

Graph databases have become increasingly popular for a variety of uses ranging from modeling online code repositories to tracking software engineering dependencies. These areas use graph databases because many of their problems can be expressed in terms of graph traversals. Recent work has applied graph databases to virtualization management, noting that many IT questions can also be expressed as graph traversals. In this paper, we study another area in which graphs are valuable: reporting and auditing in cloud infrastructure. We first examine cloud infrastructure and map its data model to a graph. Building upon this model, we recast a number of reporting queries in terms of graph traversals. We then modify the model both for performance and for accommodating additional use cases related to cloud computing, including migration from private to hybrid clouds. Our results show that while a graph backend makes it straightforward to formulate certain kinds of queries, a naive mapping of graphs to a graph database can result in poor performance. Utilizing knowledge of the problem domain and restructuring the graph can provide dramatic gains in performance and make a graph database feasible for such queries.