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Comparison of Semi-structured Data on MSSQL and PostgreSQL

2023Book part Open access
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dc.contributor.authorAlves, Leandro
dc.contributor.authorCardoso, Filipe
dc.contributor.authorOliveira, Pedro
dc.contributor.authorRocha, Júlio
dc.contributor.authorWanzeller, Cristina
dc.contributor.authorMartins, Pedro
dc.contributor.authorAbbasi, Maryam
dc.date.accessioned2024-01-10T09:27:30Z
dc.date.available2024-01-10T09:27:30Z
dc.date.issued2023
dc.description.abstractThe present study intends to compare the performance of two Data Base Management Systems, specifically Microsoft SQL Server and PostgreSQL, focusing on data insertion, queries execution, and indexation. To simulate how Microsoft SQL Server performs with key-value oriented datasets we use a converted TPC-H lineitem table. The data set is explored in two different ways, firsts using the key-value-like format and second in JSON format. The same dataset is applied to PostgreSQL DBMS to analyse performance and compare both database engines. After testing the load process on both databases, performance metrics (execution times) are obtained and compared. Experimental results show that, in general, inserts are approximately twice times faster in Microsoft SQL Server because they are injected as plain text without any type of verification, while in PostgreSQL, loaded data includes a validating process, which delays the loading process. Moreover, we did additional indexation tests, from which we concluded that in general, data loading performance degrades. Regarding query performance in PostgreSQL, we conclude that with indexation, queries become three or four percent faster, and six times faster in Microsoft SQL Server.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlves, L., Oliveira, P., Rocha, J., Wanzeller,C., Cardoso, F., Martins, P. & Abbasi, M. (2023). Comparison of Semi-structured Data on MSSQL and PostgreSQL. In J. L. Reis, M. K. Peter, J. A. Varela González, Z. Bogdanović, Z. (Eds), Marketing and Smart Technologies: Vol 337. Smart Innovation, Systems and Technologies (pp. 31-43). Springer, Singapore. https://doi.org/10.1007/978-981-19-9099-1_3pt_PT
dc.identifier.doi10.1007/978-981-19-9099-1_3pt_PT
dc.identifier.isbn978-981-19-9099-1
dc.identifier.urihttp://hdl.handle.net/10400.15/4674
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-981-19-9099-1_3pt_PT
dc.subjectKey-Valuept_PT
dc.subjectDatabasept_PT
dc.subjectMSSQLpt_PT
dc.subjectPostgreSQLpt_PT
dc.subjectTPC-Hpt_PT
dc.subjectPerformancept_PT
dc.subjectGINpt_PT
dc.subjectComputed columnspt_PT
dc.titleComparison of Semi-structured Data on MSSQL and PostgreSQLpt_PT
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage43pt_PT
oaire.citation.startPage31pt_PT
oaire.citation.volume337pt_PT
person.familyNameGonçalves Cardoso
person.givenNameFilipe
person.identifier19-AQJEAAAAJ
person.identifier.ciencia-id8219-19E8-C070
person.identifier.orcid0000-0002-3916-5182
person.identifier.scopus-author-id57486516500
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublicationf108cbea-41e4-459d-86e3-3225c293e4a6
relation.isAuthorOfPublication.latestForDiscoveryf108cbea-41e4-459d-86e3-3225c293e4a6

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