A Comparative Study of Unstructured Data with SQL and NO-SQL Database Management Systems

Abstract

This paper aims to establish a relative study between a relational Microsoft SQL Server database and a non-relational MongoDB database within the unstructured representation of data in JSON format. There is a great amount of work done regarding comparison of multiple database management applications on the basis of their performances, security etc., but we have limited information available where these databases are assessed on the basis of provided data. This study will mainly focus on looking at all the possibilities that both these database types offer us when handling data in JSON. We will accomplish this by implementing a series of experiments while taking into consideration that the subjected data does not require to be normalized; and therefore, evaluate the outcome to conclude the result.

Evaluasi Penggunaan Prometheus dan Grafana Untuk Monitoring Database Mongodb

“…DBMS sendiri diartikan sebagai perangkat lunak yang berfungsi untuk mengelola basis data sehingga pengguna dimudahkan dalam hal pengoperasian, pengolahan serta memudahkan dalam memperoleh bentuk data sesuai dengan yang diinginkan, (Malik et al, 2020).…”

Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness

“…Given that Big Data encompasses the various data types that make up a dataset, it includes datasets that contain structured, semi-structured, and unstructured data, among other things (Casado and Younas, 2015). The previous research identified that, the vast majority of the data is structured and extremely well organized (Schulze, et al, 2018), whereas in data science, many believe that managing unstructured data is one of the most difficult problems because of the tools and techniques that are successful with handling structured data are not as effective with unstructured data, which results in much confusion (Blumberg and Are, 2003;Malik, Burney and Ahmed, 2020). One of the shortcomings identified by previous research studies in dealing with mixed-up data is that it is not entirely within the control of the application running it (Alkatheeri, et al, 2020).…”

Uma proposta à gestão de estacionamentos para cidades inteligentes

“…Para superar a restrição no processamento do volume massivo de dados, a tecnologia NoSQL é capaz de lidar com uma ampla variedade de dados, incluindo formatos de gráficos, documentos e chave-valor (Malik et al, 2020). Desta forma, para se trabalhar com uma expressiva quantidade de dados e, quando sua natureza não requer um modelo relacional, uma alternativa é a adoção do banco de dados MongoDB.…”

“…Figura 1. Modelagem dos Casos de Uso O diferencial do MongoDB é que, ao invés de seguir o conceito tradicional de linhas em tabelas, uma marca registrada dos bancos de dados relacionais, o modelo do MongoDB é composto por documentos e coleções (Malik et al, 2020). Tais documentos são a unidade básica de dados neste banco, constituído pelos conjuntos de pares de chave -o identificador -e seu respectivo valor -o dado.…”