Performance analysis of relational databases MySQL, PostgreSQL and Oracle using Doctrine libraries
Marcin Choina
marcinchoina1997@gmail.comLublin University of Technology (Poland)
Maria Skublewska-Paszkowska
Lublin University of Technology (Poland)
Abstract
In modern applications, databases perform a very important function but the choice of a database system and additional libraries may affect the speed of the operations. The paper presents a time analysis concerning the performing of insert, update, delete and select operations on three database systems, MySQL 8.0, PostgreSQL 14.1 and Oracle 21c, cooperating with an application using Doctrine libraries. The obtained results showed differences between performing operations with and without object-relational mapping. In cooperation with the application, the operations were carried out the fastest using the PostgreSQL system. The Oracle system performed data selection faster without mapping on a large data set.
Keywords:
relational databases, Doctrine, ORM, PHPReferences
T. Connolly, C. Begg, Database Systems, A practical approach to Design, Implementation, and Management, sixth edition, Pearson, 2015.
Google Scholar
K. Sawłuk, M. Miłosz, Comparison of object-relational data mapping technology in Symfony 3 framework, Journal of Computer Sciences Institute 8 (2018) 235-240, https://doi.org/10.35784/jcsi.687.
DOI: https://doi.org/10.35784/jcsi.687
Google Scholar
M. Lorenz, G. Hesse, J. Rudolph, Object-relational Mapping Revised - A Guideline Review and Consolidation, Proceedings of the 11th International Joint Conference on Software Technologies - ICSOFT-EA, (2016) ISBN 978-989-758-194-6, 157-168, https://doi.org/10.5220/0005974201570168.
DOI: https://doi.org/10.5220/0005974201570168
Google Scholar
Doctrine documentation, https://www.doctrine-project.org/index.html, [03.11.2021].
Google Scholar
MySQL documentation, https://dev.mysql.com/doc/refman/8.0/en/introduction.html, [26.05.2022].
Google Scholar
Supported Platforms: MySQL Database, https://www.mysql.com/support/supportedplatforms/database.html, [24.01.2022].
Google Scholar
PostgreSQL website, https://www.postgresql.org/about/, [26.05.2022].
Google Scholar
Oracle documentation, https://docs.oracle.com/en/database/oracle/oracle-database/21/cncpt/introduction-to-oracle-database.html, [26.05.2022].
Google Scholar
A. Solarz, T. Szymczyk, Oracle 19c, SQL Server 2019, Postgresql 12 and MySQL 8 database systems comparison, Journal of Computer Sciences Institute 17 (2020) 373-378, https://doi.org/10.35784/jcsi.2281.
DOI: https://doi.org/10.35784/jcsi.2281
Google Scholar
M. Ilić, L. Kopanja, D. Zlatković, M. Trajković, D. Ćurguz, Microsoft SQL Server and Oracle: Comparative performance analysis, The 7th International conference Knowledge management and informatics (2021) 33-40.
Google Scholar
G. Dziewit, J. Korczyński, M. Skublewska-Pawszkowska, Performance analysis of relational databases Oracle and MS SQL based on desktop application, Journal of Computer Sciences Institute 8 (2018) 263-269, https://doi.org/10.35784/jcsi.693.
DOI: https://doi.org/10.35784/jcsi.693
Google Scholar
K. Islam, K. Ahsan, S. Bari, M. Saeed, S. Ali, Huge and Real-Time Database Systems: A Comparative Study and Review for SQL Server 2016, Oracle 12c & MySQL 5.7 for Personal Computer, Journal of Basic & Applied Sciences 13 (2017) 481-490, https://doi.org/10.6000/1927-5129.2017.13.79.
DOI: https://doi.org/10.6000/1927-5129.2017.13.79
Google Scholar
R. Čerešňák, M. Kvet, Comparison of query performance in relational a non-relation databases, Transportation Research Procedia 40 (2019) 170-177, https://doi.org/10.1016/j.trpro.2019.07.027.
DOI: https://doi.org/10.1016/j.trpro.2019.07.027
Google Scholar
Eloquent documentation, https://laravel.com/docs/5.0/eloquent/, [26.05.2022].
Google Scholar
R. Wodyk, M. Skublewska-Paszkowska, Performance comparison of relational databases SQL Server, MySQL and PostgreSQL using a web application and the Laravel framework, Journal of Computer Sciences Institute 17 (2020) 358-364, https://doi.org/10.35784/jcsi.2279.
DOI: https://doi.org/10.35784/jcsi.2279
Google Scholar
K. Lachewicz, Performance analysis of selected database systems: MySQL, MS SQL, PostgerSQL in the context of web applications, Journal of Computer Sciences Institute 14 (2020) 94-100, https://doi.org/10.35784/jcsi.1583.
DOI: https://doi.org/10.35784/jcsi.1583
Google Scholar
Y. Bassil, A Comparative Study on the Performance of the Top DBMS Systems, Journal of Computer Science & Research 1 (1) (2012) 20-31, https://doi.org/10.48550/arXiv.1205.2889.
Google Scholar
Authors
Maria Skublewska-PaszkowskaLublin University of Technology Poland
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