Performance analysis of selected database systems: MySQL, MS SQL, PostgerSQL in the context of web applications
Abstract
The main purpose of this article is to check which database: MySQL, MS SQL, PostgerSQL is the most efficient for Internet applications. This work contains information about the databases used, but the most important part of this article is database performance research. They are based on an application whose main task was database queries. The program was created based on new technologies, such as the Spring framework, the Hibernate library and JDBC Interface.
Keywords:
MySQL; MS SQL; PostgreSQL; database performanceReferences
[1] Marek Miłosz (red.): Aplikacje internetowe – od teorii do praktyki, 2018.
[2] Lokesh Kumar, dr. Shalini Rajawat, Krati Joshi: Comparative analysis of NoSQL (MongoDB) with MySQL Database, 2015.
[3] Sudhanshu Kulshrestha, Shelly Sachdeva, Performance comparison for data storage - Db4o and MySQL databases, 2014.
[4] Roopak K.E., Swati Rao K.S., Ritesh S., Satyadhyan: Performance Comparison of Relational Database with Object Database (DB4o), 2013
[5] Min-Gyue Jung, Seon-A Youn, Jayon Bae, Yong-Lak Choi: A Study on Data Input and Output Performance Comparison of MongoDB and PostgreSQL in the Big Data Environment, 2015.
[6] Grzegorz Dziewit, Jakub Korczyński, Maria Skublewska-Paszkowska: Analiza wydajności relacyjnych baz danych Oracle oraz MSSQL na podstawie aplikacji desktopowe, 2018.
[7] Diogo Augusto Pereira, Wagner Ourique de Morais, Edison Pignaton de Freitas: NoSQL real-time database performance comparison, 2017.
[8] Aaron Nichie, Heung-Seo Koo: A Comparison of Performance Between MSSQL Server and MongoDB for Telco Subscriber Data Management, 2016.
[9] Ken Ka-Yin Lee, Wai-Choi Tang, Kup-Sze Choi: Alternatives to relational database: Comparison of NoSQL and XML approaches for clinical data storage, 2013.
[10] Megha Katkar, Shah and Anchor Kutchhi: Performance Analysis for NoSQL and SQL, 2015.
[11] MySQL, http://vavatech.pl/technologie/bazy-danych/mysql [30.08.2019].
[12] Adam Pelikant, MS SQL Server. Zaawansowane metody programowania, 2014.
[13] PostgreSQL, http://vavatech.pl/technologie/bazy-danych/postgresql [30.08.2019].
[14] PostgreSQL 12 Released!, https://www.postgresql.org/docs/11/release-11-5.html [30.09.2019].
[15] Porównanie relacyjnych SZBD: SQLite, MySQL, PostgreSQL, https://hostovita.pl/blog/porownanie-relacyjnych-systemow-zarzadzania-bazami-danych-sqlite-mysql-postgresql/ [30.08.2019].
[16] JMeter – narzędzie testera, http://2016.testwarez.pl/jmeter-narzedzie-testera/ [ 10.09.2019].
[2] Lokesh Kumar, dr. Shalini Rajawat, Krati Joshi: Comparative analysis of NoSQL (MongoDB) with MySQL Database, 2015.
[3] Sudhanshu Kulshrestha, Shelly Sachdeva, Performance comparison for data storage - Db4o and MySQL databases, 2014.
[4] Roopak K.E., Swati Rao K.S., Ritesh S., Satyadhyan: Performance Comparison of Relational Database with Object Database (DB4o), 2013
[5] Min-Gyue Jung, Seon-A Youn, Jayon Bae, Yong-Lak Choi: A Study on Data Input and Output Performance Comparison of MongoDB and PostgreSQL in the Big Data Environment, 2015.
[6] Grzegorz Dziewit, Jakub Korczyński, Maria Skublewska-Paszkowska: Analiza wydajności relacyjnych baz danych Oracle oraz MSSQL na podstawie aplikacji desktopowe, 2018.
[7] Diogo Augusto Pereira, Wagner Ourique de Morais, Edison Pignaton de Freitas: NoSQL real-time database performance comparison, 2017.
[8] Aaron Nichie, Heung-Seo Koo: A Comparison of Performance Between MSSQL Server and MongoDB for Telco Subscriber Data Management, 2016.
[9] Ken Ka-Yin Lee, Wai-Choi Tang, Kup-Sze Choi: Alternatives to relational database: Comparison of NoSQL and XML approaches for clinical data storage, 2013.
[10] Megha Katkar, Shah and Anchor Kutchhi: Performance Analysis for NoSQL and SQL, 2015.
[11] MySQL, http://vavatech.pl/technologie/bazy-danych/mysql [30.08.2019].
[12] Adam Pelikant, MS SQL Server. Zaawansowane metody programowania, 2014.
[13] PostgreSQL, http://vavatech.pl/technologie/bazy-danych/postgresql [30.08.2019].
[14] PostgreSQL 12 Released!, https://www.postgresql.org/docs/11/release-11-5.html [30.09.2019].
[15] Porównanie relacyjnych SZBD: SQLite, MySQL, PostgreSQL, https://hostovita.pl/blog/porownanie-relacyjnych-systemow-zarzadzania-bazami-danych-sqlite-mysql-postgresql/ [30.08.2019].
[16] JMeter – narzędzie testera, http://2016.testwarez.pl/jmeter-narzedzie-testera/ [ 10.09.2019].
Lachewicz, K. (2020). Performance analysis of selected database systems: MySQL, MS SQL, PostgerSQL in the context of web applications. Journal of Computer Sciences Institute, 14, 94–100. https://doi.org/10.35784/jcsi.1583
Authors
Katarzyna Lachewiczkatarzyna.lachewicz@pollub.edu.pl
Lublin University of Technology Poland
Statistics
Abstract views: 1275PDF downloads: 1434
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
