Modeling and Management Big Data in Databases—A Systematic Literature Review

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Title: Modeling and Management Big Data in Databases—A Systematic Literature Review
Authors: Martinez-Mosquera, Diana | Navarrete, Rosa | Luján-Mora, Sergio
Research Group/s: Advanced deveLopment and empIrical research on Software (ALISoft)
Center, Department or Service: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos
Keywords: Big data | Management | Modeling | Literature review
Knowledge Area: Lenguajes y Sistemas Informáticos
Issue Date: 15-Jan-2020
Publisher: MDPI
Citation: Martinez-Mosquera D, Navarrete R, Lujan-Mora S. Modeling and Management Big Data in Databases—A Systematic Literature Review. Sustainability. 2020; 12(2):634. doi:10.3390/su12020634
Abstract: The work presented in this paper is motivated by the acknowledgement that a complete and updated systematic literature review (SLR) that consolidates all the research efforts for Big Data modeling and management is missing. This study answers three research questions. The first question is how the number of published papers about Big Data modeling and management has evolved over time. The second question is whether the research is focused on semi-structured and/or unstructured data and what techniques are applied. Finally, the third question determines what trends and gaps exist according to three key concepts: the data source, the modeling and the database. As result, 36 studies, collected from the most important scientific digital libraries and covering the period between 2010 and 2019, were deemed relevant. Moreover, we present a complete bibliometric analysis in order to provide detailed information about the authors and the publication data in a single document. This SLR reveal very interesting facts. For instance, Entity Relationship and document-oriented are the most researched models at the conceptual and logical abstraction level respectively and MongoDB is the most frequent implementation at the physical. Furthermore, 2.78% studies have proposed approaches oriented to hybrid databases with a real case for structured, semi-structured and unstructured data.
ISSN: 2071-1050
DOI: 10.3390/su12020634
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Peer Review: si
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Appears in Collections:INV - ALISoft - Artículos de Revistas

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