Graph Database and Relational Database Performance Comparison on a Transportation Network

Jinhua Chen, Qingyu Song, Can Zhao, Zhiheng Li

Abstract: Facing the problem of structuring irregular data in the big data era, graph databases are a powerful solution to handle link relationship without costly operations and enjoy great flexibility as data model changes. Though it’s well-known that graph databases have superior performance in a certain area than relational databases, little effort has been put into investigating the detail of these advantages. In this paper, we report a systematic performance study of graph databases and relational databases on a transportation network. We design a database benchmark considering traversal and searching performance to evaluate system performance in different data organizations, initial states, and running modes. Our results show that graph databases outperform relational databases system in three main graph algorithms testing. Furthermore, we discuss the reasonable practice in applications based on graph databases from our experiment results.