Response time analysis on indexing in relational databases and their impact Sam Pettersson & Martin Borg 18, June, 2020 Dept. Computer Science & Engineering Blekinge Institute of Technology SE–371 79 Karlskrona, Sweden This thesis is submitted to the Faculty of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the bachelor’s degree in software engineering. The thesis is equivalent to 10 weeks of full-time studies. Contact Information: Authors: Martin Borg E-mail:
[email protected] Sam Pettersson E-mail:
[email protected] University advisor: Associate Professor. Mikael Svahnberg Dept. Computer Science & Engineering Faculty of Computing Internet : www.bth.se Blekinge Institute of Technology Phone : +46 455 38 50 00 SE–371 79 Karlskrona, Sweden Fax : +46 455 38 50 57 Abstract This is a bachelor thesis concerning the response time and CPU effects of indexing in relational databases. Analyzing two popular databases, PostgreSQL and MariaDB with a real-world database structure us- ing randomized entries. The experiment was conducted with Docker and its command-line interface without cached values to ensure fair outcomes. The procedure was done throughout seven different create, read, update and delete queries with multiple volumes of database en- tries to discover their strengths and weaknesses when utilizing indexes. The results indicate that indexing has an overall enhancing effect on almost all of the queries. It is found that join, update and delete op- erations benefits the most from non-clustered indexing. PostgreSQL gains the most from indexes while MariaDB has less of an improvement in the response time reduction.