NoSQL Database Classification: New Era of Databases for Big Data

NoSQL Database Classification: New Era of Databases for Big Data

Biswaranjan Acharya, Ajaya Kumar Jena, Jyotir Moy Chatterjee, Raghvendra Kumar, Dac-Nhuong Le
Copyright: © 2019 |Pages: 16
DOI: 10.4018/IJKBO.2019010105
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Abstract

The rapid growth in the digital world in form of exponentiation to accommodate huge amount of structured, semi-structured, unstructured and hybrid data received from different sources. By using the conventional data management tools, it is quite impossible to manage this semi-structured and unstructured data for which a non-relational database management system such as NoSQL and NewSQL are used to handle such types of data. These types of semi-structured and structured data are generally considered ‘Big Data.' This article describes the basic characteristics, background and the models of NoSQL used for big data applications. In this work, the authors surveyed different NoSQL characteristics used by the researchers and try to compare the strength and weakness of different NoSQL databases.
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2. Background

The basic goal of Relational Database Management System (DBMS) is to use data processing in business applications to store the business transactions data, financial records and personal data related to an organisation (Browne). The traditional database stores the data in the form of relational tables which is applicable only for structured data. So there is a challenge to deal with semi-structured and unstructured data (Han, Haihong & Le et al., 2011). As a result of which people have adopted variety of non-relational databases referred as NoSQL (Du et al., 2010).The primary advantages of NoSql are mainly quick accessibility, storing massive data and also easy to expand with low cost (Tudorica & Burcer, 2011). The characteristics of NoSQL database can be given in Figure 1.

Figure 1.

Characteristics of NoSQL database

IJKBO.2019010105.f01

The CAP theorem described the conflicts between the distinctive parts of high accessibility in dispersed frameworks that are not completely feasible (Potter, 1985):

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