Scheme mapping for relational database transformation to ontology: A survey

Author(s):  
Paramita Mayadewi ◽  
Benhard Sitohang ◽  
Fazat N. Azizah
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zain Aftab ◽  
Waheed Iqbal ◽  
Khaled Mohamad Almustafa ◽  
Faisal Bukhari ◽  
Muhammad Abdullah

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.


2020 ◽  
Vol 10 (3) ◽  
pp. 759-766 ◽  
Author(s):  
Matěj Karolyi ◽  
Martin Komenda ◽  
Luke Woodham ◽  
Jakub Ščavnický ◽  
Christos Vaitsis ◽  
...  

1996 ◽  
Vol 8 (3) ◽  
pp. 160-168 ◽  
Author(s):  
Janet Burt ◽  
Tom Beaumont James

This article discusses the different approaches to the treatment of historical databases: the relational database system and κλειω, a source-oriented approach.


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