Comparative analysis of selected databases on the example of a proprietary web application
Łukasz Przychodzień
lukasz.przychodzien@pollub.edu.plLublin University of Technology (Poland)
Dominika Radwan
Lublin University of Technology (Poland)
Grzegorz Kozieł
Lublin University of Technology (Poland)
Abstract
Database performance is one of the most important factors affecting the usability of the system. Therefore, the authors of the article decided to examine 3 popular database systems: MySQL, MS SQL and PostgreSQL, analyzing their performance. For this purpose, a test application was prepared and Docker software was used to simulate different hardware parameters. Depending on the selected settings and the number of records, different results were obtained. For small data sets, the differences were almost imperceptible. They have drastically increased for large data sets. In this case, MySQL fared poorly, and MS SQL was the best. This means that the choice of the database is very important, and it is worth considering the available hardware, the amount of data and the queries performed.
Keywords:
performance analysis, DBMS, relational databasesReferences
R. Wodyk, M. Skublwska-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
G. Dziewit, J. Korczyński, M. Skublewska-Paszkowska, 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
S. Stets, G. Kozieł, Analiza porównawcza baz danych – praca dyplomowa magisterska, Politechnika Lubelska, Lublin 2019.
Google Scholar
K. Krocz, O. Kizun, M. Skublewska-Paszkowska, Analiza wydajności relacyjnych baz danych MySQL, PostgreSQL, MariaDB oraz H2 – praca dyplomowa magisterska, Politechnika Lubelska, Lublin 2020.
Google Scholar
S. Tongkaw, A. Tongkaw, A comparison of database performance of MariaDB and MySQL with OLTP workload, IEEE Conference on Open Systems, Langkawi 2016, 117-119.
DOI: https://doi.org/10.1109/ICOS.2016.7881999
Google Scholar
C. -O. Truica, F. Radulescu, A. Boicea and I. Bucur, Performance Evaluation for CRUD Operations in Asynchronously Replicated Document Oriented Database, 20th International Conference on Control Systems and Computer Science, Bucharest 2015, 191-196.
DOI: https://doi.org/10.1109/CSCS.2015.32
Google Scholar
P. Beynon-Davies, Systemy baz danych, Wydawnictwa Naukowo Techniczne, 2003.
Google Scholar
Strefa wiedzy Vavatech, https://vavatech.pl/technologie/bazy-danych/mysql, [10.02.2023].
Google Scholar
MySQL - Wikipedia, https://en.wikipedia.org/wiki/MySQL, [10.02.2023].
Google Scholar
Opis oprogramowania PostgreSQL, https://www.postgresql.org/about/, [12.02.2023].
Google Scholar
PostgreSQL - Amazon AWS, https://aws.amazon.com/rds/postgresql/what-is-postgresql/, [12.02.2023].
Google Scholar
Microsoft SQL Server - Wikipedia, https://pl.wikipedia.org/wiki/Microsoft_SQL_Server, [20.04.2023].
Google Scholar
Opis systemu MS SQL na portalu Atlantic, https://www.atlantic.net/vps-hosting/what-is-mssql/, [21.04.2023].
Google Scholar
Konfiguracja kontenera Docker, https://www.baeldung.com/ops/docker-memory-limit, [21.03.2023].
Google Scholar
Authors
Łukasz Przychodzieńlukasz.przychodzien@pollub.edu.pl
Lublin University of Technology Poland
Authors
Dominika RadwanLublin University of Technology Poland
Authors
Grzegorz KoziełLublin University of Technology Poland
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