Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/42343

TitleData models in NoSQL databases for big data contexts
Author(s)Santos, Maribel Yasmina
Costa, Carlos
KeywordsBig Data
Data Model
Data Warehousing
NoSQL Databases
Issue dateJun-2016
PublisherSpringer Verlag
JournalLecture Notes in Computer Science
CitationSantos, Maribel Yasmina and Carlos Costa, “Data Models in NoSQL Databases for Big Data Contexts”, Proceedings of the 2016 International Conference of Data Mining and Big Data, Springer-Verlag, LNCS 9714, pp 475-485, June 25-30, Bali, Indonesia, 2016 (DOI:10.1007/978-3-319-40973-3_48).
Abstract(s)Data models are a central piece in information systems, being the relational data models very popular and extensively used. In Big Data, and due to the characteristics of the NoSQL databases, the data modeling task is seen in another perspective, as those databases are considered schema-free. Nevertheless, these databases also need data models that ensure the proper storage and querying of the data. Considering the vast amount of relational databases and the ever-increasing volume of data, the importance of data models in Big Data increases. In this work, a specific set of rules is proposed for the automatic transition between a traditional and a Big Data environment, considering two specific objectives: the identification of a columnar data model for HBase supporting operational needs and the identification of a tabular data model for Hive supporting analytical needs. The obtained results show the applicability of the proposed rules and their relevance for data modeling in Big Data environments.
TypeConference paper
URIhttp://hdl.handle.net/1822/42343
ISBN978-3-319-40973-3
DOI10.1007/978-3-319-40973-3_48
ISSN0302-9743
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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