dc.contributor.author | Güney E. | |
dc.contributor.author | Ceylan N. | |
dc.date.accessioned | 2023-03-14T20:29:01Z | |
dc.date.available | 2023-03-14T20:29:01Z | |
dc.date.issued | 2022 | |
dc.identifier.isbn | 9.78303E+12 | |
dc.identifier.issn | 1867-8211 | |
dc.identifier.uri | https://doi.org/10.1007/978-3-031-01984-5_15 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14002/1564 | |
dc.description | 1st International Congress of Electrical and Computer Engineering, ICECENG 2022 -- 9 February 2022 through 12 February 2022 -- -- 277759 | en_US |
dc.description.abstract | Today, phones, tablets, commercial software, and many different devices are constantly generating data. These produced data should be accessed later on, such as software in business processes or business intelligence. Therefore, these generated data must be stored. There are many popular ways to store data constantly growing in size. All these options come with certain advantages and disadvantages. In this study, a performance comparison will be made between the PostgreSQL database, which is one of the relational databases used for data storage for many years, and the MongoDB database, which is one of the document databases, which has become increasingly popular in recent years, in certain test scenarios. In addition, the properties of relational databases and document databases are given. As a result of the study, similar data and test scenarios created in two databases and different test scenarios in terms of performance were examined, and response times were compared. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer Science and Business Media Deutschland GmbH | en_US |
dc.relation.ispartof | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | MongoDB | en_US |
dc.subject | NoSQL database | en_US |
dc.subject | PostgreSQL | en_US |
dc.subject | Relational database | en_US |
dc.subject | Business Process | en_US |
dc.subject | Commercial software | en_US |
dc.subject | Data storage | en_US |
dc.subject | Document database | en_US |
dc.subject | MongoDB | en_US |
dc.subject | Performance comparison | en_US |
dc.subject | PostgreSQL | en_US |
dc.subject | Relational Database | en_US |
dc.subject | Test scenario | en_US |
dc.subject | Time comparison | en_US |
dc.subject | Digital storage | en_US |
dc.title | Response Times Comparison of MongoDB and PostgreSQL Databases in Specific Test Scenarios | en_US |
dc.type | conferenceObject | en_US |
dc.department | Belirlenecek | en_US |
dc.identifier.doi | 10.1007/978-3-031-01984-5_15 | |
dc.identifier.volume | 436 LNICST | en_US |
dc.identifier.startpage | 178 | en_US |
dc.identifier.endpage | 188 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57696129400 | |
dc.authorscopusid | 57698288000 | |
dc.identifier.scopus | 2-s2.0-85130305615 | en_US |