GDBApex: A graph-based system to enable efficient transformation of enterprise infrastructures

摘要

Graph-based database engines have been developed by different researchers and companies. Many optimization methods have been integrated within these engines to enable fast and efficient data processing. However, many small- and medium-size organizations have not changed their database infrastructures and still rely on a relational management modeling approach. This limits their service performance, especially in today's large-scale data processing requirements. Transformation to the use of graph-based modeling and design is not a straightforward process. In order to make a successful transformation, correct process semantics as well as the design of vertices, edges, labels, and process relations are required. The goal of this article is to help small- and medium-size organizations make this transformation successful in order to satisfy customers' expectations and meet the requirements of data-intensive applications. The proposed graph-based modeling approach uses a graph structure for semantic queries and applies software engineering design principles. Moreover, it provides a case study with many data transactions. The system outperformed relational database management systems by an order of magnitude. Scalability of the system is examined and compared with the regular relational-based modeling. In addition, a load balancing solution is used to achieve high scalability.