Comparative analysis of connection performance with databases via JDBC interface and ORM programming frameworks
Mateusz Żuchnik
mateusz.zuchnik@pollub.edu.plLublin University of Technology (Poland)
Piotr Kopniak
Lublin University of Technology (Poland)
Abstract
The research subject of this paper was the comparative analysis of efficiency of connections with databases using different communication methods based on Java programming language. The tools investigated included JDBC drivers and Object-relational mapping (ORM) frameworks. A survey based on 8 different criteria was conducted to determine the most effective method and tool for working with relational databases when developing Java applications. The weights of the criteria were determined through a survey of Java programmers and computer science students.
Keywords:
database connections, Java, performane, ORM frameworkReferences
Główny urząd statystyczny, społeczeństwo informacyjne w Polsce w 2020 roku, https://stat.gov.pl/obszary-tematyczne/nauka-i-technika-spoleczenstwo-informacyjne/spoleczenstwo-informacyjne/spoleczenstwo-informacyjne-w-polsce-w-2020-roku,1,14.html , [17.09.2021].
Google Scholar
J. Desjardins, How much data is generated each day?, World Economic Forum 2019, https://www.weforum.org/agenda/2019/04/how-much-data-is-generated-each-day-cf4bddf29f/ , [17.09.2021].
Google Scholar
Dokumentacja programistyczna ODBC, https://docs.microsoft.com/en-us/sql/odbc/reference/odbc-programmer-s-reference?view=sql-server-ver15 , [19.09.2021].
Google Scholar
Dokumentacja programistyczna JDBC, https://docs.oracle.com/cd/E11882_01/java.112/e16548/toc.htm , [19.09.2021].
Google Scholar
P. Błoch, M. Wojciechowski, Analiza porównawcza technologii odwzorowania obiektowo-relacyjnego dla aplikacji Java. XIII Konferencja PLOUG: Systemy informatyczne. Projektowanie, implementowanie, eksploatowanie, Zakopane (2007).
Google Scholar
K. Jóźwicka, M. Mitrus, Hybrydowe metody pracy z bazami danych w aplikacjach JEE. Journal of Computer Sciences Institute, (2019) 12.
DOI: https://doi.org/10.35784/jcsi.433
Google Scholar
M. Grzesińska, M. Waszczyńska, B. Pańczyk, JEE DATABASE APPLICATIONS PERFORMANCE. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 6(4) (2016) 73-76.
Google Scholar
Liczba wyszukiwań badanych narzędzi w serwisie Google, https://trends.google.pl/trends/explore?q=jdbc,jooq,mybatis,hibernate , [20.09.2021].
Google Scholar
Dokumentacja techniczka Spring Data, https://docs.spring.io/spring-data/jpa/docs/current/reference/html/#reference ,[20.09.2021].
Google Scholar
Dokumentacja techniczna systemu bazodanowego MySQL, https://dev.mysql.com/doc/ , [17.09.2021].
Google Scholar
G. Reese, Database Programming with JDBC and JAVA, O’Reilly Media Inc (2000).
Google Scholar
K. Siva Prasad Reddy, Working with JOOQ. In: Begin-ning Spring Boot 2, Apress, Berkeley CA (2017) 71-82.
DOI: https://doi.org/10.1007/978-1-4842-2931-6_7
Google Scholar
K. Siva Prasad Reddy, Java Persistence with MyBatis3, Packt Publishing Ltd (2013).
Google Scholar
Dokumentacja Java Persistence API, https://javadoc.io/doc/javax.persistence/javax.persistence-api/latest/index.html , [20.09.2021].
Google Scholar
P. T. Fisher, B. D. Murphy, Spring persistence with Hibernate, Apress (2010).
DOI: https://doi.org/10.1007/978-1-4302-2633-8_4
Google Scholar
J. Clarke-Salt, SQL injection attacks and defense, Elsevier (2009).
DOI: https://doi.org/10.1016/B978-1-59749-424-3.00004-9
Google Scholar
C. Walls, Spring Boot in action, Manning Publications (2016).
Google Scholar
N. Kumari, R. Kumar, Profiling JVM for AI Applications Using Deep Learning Libraries, In Machine Learning for Predictive Analysis, Springer, Singapore (2021) 395-404.
DOI: https://doi.org/10.1007/978-981-15-7106-0_39
Google Scholar
Authors
Piotr KopniakLublin University of Technology Poland
Statistics
Abstract views: 406PDF downloads: 416
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.