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.
Primary Language | English |
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Subjects | Computer Software |
Journal Section | Research Article |
Authors | |
Early Pub Date | June 10, 2022 |
Publication Date | June 23, 2022 |
Submission Date | May 12, 2021 |
Published in Issue | Year 2022 Volume: 8 Issue: 2 |
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