Efficient data management tools for the heterogeneous big data warehouse

Efficient data management tools for the heterogeneous big data warehouse

Bibliographic Details
Parent link:Physics of Particles and Nuclei Letters: Scientific Journal
Vol. 13, iss. 5.— 2016.— [P. 689–692]
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра оптимизации систем управления (ОСУ) Научно-учебная лаборатория "Виртуальный промысел" (НУЛ ВП)
Other Authors: Alekseev A. A. Aleksandr Aleksandrovich, Osipova V. V. Viktoriya Viktorovna, Ivanov M. A. Maksim Anatoljevich, Klimentov A. A. Aleksey Anatoljevich, Grigorjeva N. V. Nina Valerjevna, Nalamvar H. S. Hitesh Sanzhay
Summary:Title screen
The traditional RDBMS has been consistent for the normalized data structures. RDBMS served well for decades, but the technology is not optimal for data processing and analysis in data intensive fields like social networks, oil-gas industry, experiments at the Large Hadron Collider, etc. Several challenges have been raised recently on the scalability of data warehouse like workload against the transactional schema, in particular for the analysis of archived data or the aggregation of data for summary and accounting purposes. The paper evaluates new database technologies like HBase, Cassandra, and MongoDB commonly referred as NoSQL databases for handling messy, varied and large amount of data. The evaluation depends upon the performance, throughput and scalability of the above technologies for several scientific and industrial use-cases. This paper outlines the technologies and architectures needed for processing Big Data, as well as the description of the back-end application that implements data migration from RDBMS to NoSQL data warehouse, NoSQL database organization and how it could be useful for further data analytics.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2016
Subjects:
электронный ресурс
труды учёных ТПУ
СУБД
система управления базами данных
Relational Database Management System
RDBMS
NoSQL
SQL
Big Data
Heterogeneous Data Warehouse
хранилища
данные
Apache Hadoop
Hive
MongoDB
Data Manipulation Language
DML
Online Access:http://dx.doi.org/10.1134/S1547477116050022
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=653282

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