R&D: Database Storage Format for High Performance Analytics of Immutable Data
Paper includes developed storage formats, data load and extraction algorithms and performance measurements.
This is a Press Release edited by StorageNewsletter.com on June 9, 2021 at 2:31 pmIEEE Xplore has published, in 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) proceedings, an article written by Mikhail M. Rovnyagin, Sviatoslav O. Dmitriev, Alexander S. Hrapov, Artem A. Maksutov, and Igor A. Turovskiy, National Research Nuclear University ‘MEPhI’, Moscow, Russian Federation.
Abstract: “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.“
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