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Database Storage Format for High Performance Analytics of Immutable Data

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dc.contributor.authorRovnyagin, M. M.
dc.contributor.authorDmitriev, S. O.
dc.contributor.authorHrapov, A. S.
dc.contributor.authorMaksutov, A. A.
dc.contributor.authorTurovskiy, I. A.
dc.contributor.authorРовнягин, Михаил Михайлович
dc.contributor.authorДмитриев, Святослав Олегович
dc.contributor.authorХрапов, Александр Сергеевич
dc.contributor.authorМаксутов, Артем Артурович
dc.date.accessioned2024-11-29T15:23:40Z
dc.date.available2024-11-29T15:23:40Z
dc.date.issued2021
dc.description.abstract© 2021 IEEE.Most of modern database management systems offer a set of data manipulation operations, which strictly limits the available methods of data storage optimization. This article describes a database storage format that provides a low latency access to stored data with highly optimized sequential data extraction process by prohibiting any data modification after initially loading the data. The current study is aimed at developing a database management system that is suitable for high performance analytics of immutable data and performs better than database management systems with wider applicability. This paper includes developed data storage formats, data load and extraction algorithms and performance measurements.
dc.format.extentС. 618-622
dc.identifier.citationDatabase Storage Format for High Performance Analytics of Immutable Data / Rovnyagin, M.M. [et al.] // Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2021. - 2021. - P. 618-622. - 10.1109/ElConRus51938.2021.9396453
dc.identifier.doi10.1109/ElConRus51938.2021.9396453
dc.identifier.urihttps://www.doi.org/10.1109/ElConRus51938.2021.9396453
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85104802868&origin=resultslist
dc.identifier.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000669709800137
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/23968
dc.relation.ispartofProceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2021
dc.titleDatabase Storage Format for High Performance Analytics of Immutable Data
dc.typeConference Paper
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