Abstract: In recent days, the demand for dealing large set of distributed data obsoletes the relational database and its structured query language (SQL) solutions in practice and paves the way for novel solutions in the name of non-relational database as not-only SQL (NoSQL). The NoSQL offers dynamic, flexible, scalable, highly available, greater performance and near real-time access to the distributed nature of voluminous data used for current industrial applications. Apart from these giant features of NoSQL, the SQL is still found to be in operation because of its popularity and standard. This paper projected an algorithm to convert the relational documents of MySQL into any document oriented NoSQL databases automatically without destructing the existing relational database setup and installing the NoSQL from scratch in the core machines. Java Script Object Notation (JSON) is a human readable data interchange format, being used in web development. The characteristics of JSON widened its use cases from web development to database storage. The Mongo DB, one of the most popular document oriented NoSQL adapts JSON format for its storage. The proposed algorithm is built based on its schema definition and the performance is captured through evaluating it against a sample database from hospital management system. The findings are discussed with great interest of addressing the challenges and revealing the scope for improvement.

K. Revathi, T. Tamilselvi, Batini Dhanwanth and M. Dhivya, “Auto JSON: An Automatic Transformation Model for Converting Relational Database to Non-relational Documents” International Journal of Advanced Computer Science and Applications(IJACSA), 14(3), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140377

@article{Revathi2023,
title = {Auto JSON: An Automatic Transformation Model for Converting Relational Database to Non-relational Documents},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140377},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140377},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {3},
author = {K. Revathi and T. Tamilselvi and Batini Dhanwanth and M. Dhivya}
}