Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3656
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dc.contributor.authorUzunbayır, Serhat-
dc.date.accessioned2023-06-16T15:01:53Z-
dc.date.available2023-06-16T15:01:53Z-
dc.date.issued2022-
dc.identifier.isbn9.78167E+12-
dc.identifier.urihttps://doi.org/10.1109/UBMK55850.2022.9919589-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/3656-
dc.description7th International Conference on Computer Science and Engineering, UBMK 2022 -- 14 September 2022 through 16 September 2022 -- 183844en_US
dc.description.abstractThe importance of big data, one of the most popular and researched topics of today, has been a subject of constant debate. Big data appear in almost every aspect of our lives, such as healthcare, education, shopping, social media, and industry; however, its storage and processing is not very efficient when using traditional methods. Therefore, the aim of this study is to obtain big data using a novel social shopping application that collects data from its users. The application is designed to collect information about people, products, and friendships among people, as well as product relationships, and post creations, and also enables setting up various options to mark products, such as like, buy, have, or help. The data gathered by the system is analyzed using both relational and non-relational databases, and the performance of these databases is then compared using specific queries, to reveal the model which performs better and more efficiently. Three different database models were designed and implemented for the system; a relational database, a document database, and a graph database. As a result of the experiments, there is no single model that is superior to the others as all three databases have their advantages and disadvantages. Therefore, the database selection should be decided based on the application domain. © 2022 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectbig dataen_US
dc.subjectdocument databaseen_US
dc.subjectgraph databaseen_US
dc.subjectnosqlen_US
dc.subjectrelational databasesen_US
dc.subjectBig dataen_US
dc.subjectDigital storageen_US
dc.subjectQuery languagesen_US
dc.subjectBig data applicationsen_US
dc.subjectDocument databaseen_US
dc.subjectGraph databaseen_US
dc.subjectHealth care educationen_US
dc.subjectMongoDBen_US
dc.subjectNon-Relational Databasesen_US
dc.subjectNosqlen_US
dc.subjectPerformanceen_US
dc.subjectRelational Databaseen_US
dc.subjectSocial mediaen_US
dc.subjectGraph Databasesen_US
dc.titleRelational Database and NoSQL Inspections using MongoDB and Neo4j on a Big Data Applicationen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/UBMK55850.2022.9919589-
dc.identifier.scopus2-s2.0-85141885837en_US
dc.authorscopusid57205586949-
dc.identifier.startpage148en_US
dc.identifier.endpage153en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.grantfulltextreserved-
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept05.04. Software Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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