Modeling and Management of Big Data in Databases

1. Introduction

The Big Data modeling term became widespread in 2011, as is visible in Figure 1. This figure shows searches in Google Trends related to Big Data modeling, which are intensified from 2011 onwards. Searches before 2004 are not presented, since Google Trends does not store earlier data. In recent years, researchers have consolidated their efforts to study new paradigms to deal with Big Data. Thus, novel Big Data modeling and management in databases approaches have emerged, in line with the new requirements. In consequence, new techniques in the database context have evolved towards Not Only SQL (NoSQL).

The work presented in this paper is motivated by the acknowledgment that a complete systematic literature review (SLR) that consolidates all the research efforts for Big Data modeling and management in databases is missing. An SLR is the best way to collect, summarize and evaluate all scientific evidence about a topic. It allows for the description of research areas shown the greatest and least interest by researchers. Considering the exposed issues, the SLR conducted in this work can contribute to solving this lack by collecting and analyzing details about the research published from 2010 to 2019. As a basis for our SLR, we adhered to the guidelines proposed by Kitchenham. Moreover, this paper presents a complete bibliometric analysis and summarizes existing evidence about research on Big Data modeling and management in databases. With the information attained from the analysis performed, we will identify trends and gaps in the published research to provide a background for new research. As result, 1376 papers were obtained from scientific libraries and 36 studies were selected as relevant. All the research efforts were mapped in order to respond the three research questions defined in this research. Our main goal is to consolidate the main works to provide an awareness of the trends and the gaps related to Big Data modeling.

The remainder of this paper is organized as follows. First is the Introduction section, containing the meaning of the different terms discussed in this study. Second, a Method section presents the process used to perform the planning, conducting and reporting of the SLR. The planning phase describes the identification of the need for a SLR study and the development of a review protocol, objectives and justification, research questions and strategy. The conducting phase presents the inclusion and selection criteria for the final corpus of selected studies.

Third, the Results section answers the research questions in three subsections. The first subsection, the Bibliometric Analysis, comprises the reporting stage, including authors' information, such as affiliation and country and relevant data about their works; for instance, publication information, number of citations, funding source, year, digital library, impact factor, ranking. The second subsection, the Systematic Literature Review, presents a mapping of the selected studies according to three key concepts in a concept matrix regarding to the dataset source, modeling and database. The third subsection, the Discussion, highlights relevant findings in the SLR study in order to identify existing trends and gaps. Finally, conclusions and future works are presented.

Figure 1. Trend of use of term Big Data.