Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping
Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intellige...
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doaj-5dd7790001ce423d88666f30d3b8721f2021-07-02T15:36:03ZengHindawi LimitedScientific Programming1058-92441875-919X2020-01-01202010.1155/2020/88133508813350Automatic NoSQL to Relational Database Transformation with Dynamic Schema MappingZain Aftab0Waheed Iqbal1Khaled Mohamad Almustafa2Faisal Bukhari3Muhammad Abdullah4Punjab University College of Information Technology (PUCIT), University of the Punjab, Lahore, PakistanPunjab University College of Information Technology (PUCIT), University of the Punjab, Lahore, PakistanCollege of Computer and Information Sciences, Prince Sultan University Riyadh, 11586 Riyadh, Saudi ArabiaPunjab University College of Information Technology (PUCIT), University of the Punjab, Lahore, PakistanPunjab University College of Information Technology (PUCIT), University of the Punjab, Lahore, PakistanRecently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database.http://dx.doi.org/10.1155/2020/8813350 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zain Aftab Waheed Iqbal Khaled Mohamad Almustafa Faisal Bukhari Muhammad Abdullah |
spellingShingle |
Zain Aftab Waheed Iqbal Khaled Mohamad Almustafa Faisal Bukhari Muhammad Abdullah Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping Scientific Programming |
author_facet |
Zain Aftab Waheed Iqbal Khaled Mohamad Almustafa Faisal Bukhari Muhammad Abdullah |
author_sort |
Zain Aftab |
title |
Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping |
title_short |
Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping |
title_full |
Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping |
title_fullStr |
Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping |
title_full_unstemmed |
Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping |
title_sort |
automatic nosql to relational database transformation with dynamic schema mapping |
publisher |
Hindawi Limited |
series |
Scientific Programming |
issn |
1058-9244 1875-919X |
publishDate |
2020-01-01 |
description |
Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database. |
url |
http://dx.doi.org/10.1155/2020/8813350 |
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