Abstract
Over decades, relational database management systems (RDBMSs) have been the first choice to manage data. Recently, due to the variety properties of big data, graph database management systems (GDBMSs) have emerged as an important complement to RDBMSs. As pointed out in the existing literature, both RDBMSs and GDBMSs are capable of managing graph data and relational data; however, the boundaries of them still remain unclear. For this reason, in this paper, we first extend a unified benchmark for RDBMSs and GDBMSs over the same datasets using the same query workload under the same metrics. We then conduct extensive experiments to evaluate them and make the following findings: (1) RDBMSs outperform GDMBSs by a substantial margin under the workloads which mainly consist of group by, sort, and aggregation operations, and their combinations; (2) GDMBSs show their superiority under the workloads that mainly consist of multi-table join, pattern match, path identification, and their combinations.
Highlights
From the perspective of relational database management systems (RDBMSs), RDBMSs have been proved to be capable of dealing with graph data management and analysis, and a few recent works have shown that by extending SQL languages in RDBMSs to support graph operations, the performance is comparable between RDBMSs and graph database management systems (GDBMSs) [10,11,12,13,14], verifying this capacity of RDBMSs
– We extend a unified benchmark for both RDBMSs and GDBMSs to evaluate them under the same datasets as well as the same metrics
To gain a better understanding, we further provide two examples of the transformations from primitive operations in RDBMSs to their counterpart in GDBMSs which are shown in Algorithm 1 and Algorithm 2, respectively
Summary
From the perspective of GDBMSs, their advantage lies in schema-less property They are able to manage structured, unstructured, or semi-structured data and are more flexible than RDBMSs. Given that GDBMSs are able to manage relational data, it is argued that RDBMSs may be replaced by GDBMSs. On the other hand, from the perspective of RDBMSs, RDBMSs have been proved to be capable of dealing with graph data management and analysis, and a few recent works have shown that by extending SQL languages in RDBMSs to support graph operations, the performance is comparable between RDBMSs and GDBMSs [10,11,12,13,14], verifying this capacity of RDBMSs. due to the lack of a unified graph model and query language across GDBMSs, which often incurs an extra programming and maintenance overhead for users, the necessity of GDBMSs is disputed.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
