Analyzing The Encountered Problems and Possible Solutions of Converting Relational Databases to Graph Databases

Abstract

Relational database management systems have been used for storing data for a long time. However, these systems are insufficient to analyze the large and complex structure of the data. Graph databases are becoming more common day by day due to their capacity to contribute to the analysis. Also, graph databases are better at modeling and querying complex relationships than relational databases. To use graph databases with old data stored in relational databases a transfer process is needed. In this study, the problems to be encountered in transferring the data stored in a relational database to a graph database were examined and methods that could be used as solutions to them were proposed. In addition, it is aimed to prevent data loss and data inconsistency that may occur with design errors in relational databases. For this purpose, the normalization process needs to be applied to a relational database before transferring data to a graph database. In our study, we developed a method that converts data to the first normal form during the transfer. But for better data consistency in practice third normal form is the minimum requirement. By using the functional dependencies found, it is possible to make relational databases suitable for higher normal forms. For functional dependency detection, which is normally a very time-consuming and costly process, we developed a method based on a graph database.

Keywords

• Relational database
• graph database
• normalization
• normal form
• functional dependency

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