Mapping and Conversion between Relational and Graph Databases Models: A Systematic Literature Review

Abstract

Given the current mass of information and, considering that such information is increasingly related, \the use of a graph model to represent Storing these can make it easier to identify information that would be hard to see when using a relational model. The purpose of this study is to characterize the existing techniques about the mapping and conversion process between relational and graph-oriented database models. For this, a systematic literature review was performed in the Scopus and IEEE Xplore databases. We validated 11 articles that were included in the period from 1 January 2013 to 31 May 2019. The results showed that most studies try to perform the mapping and migration process with different algorithms and data structures and each one has a point of failure, such as data loss, test execution distributed environments and other Relational DBMSs. The contribution of this research is to situate the state of the art of the conversion process between relational and graph-oriented databases, highlighting the positive and negative points of the existing techniques, with the objective of developing algorithms that combine the best of each technique, improving the existing failures.