Storage Facility Management Framework Using NoSQL Database for Healthcare Sector

Authors

  • Hannah A. Amoniah Lecturer, Department of Computer Science, Rivers State University, Port Harcourt, Rivers State, Nigeria
  • Matthias Daniel Lecturer, Department of Computer Science, Rivers State University, Port Harcourt, Rivers State, Nigeria
  • E. O. Bennett Lecturer, Department of Computer Science, Rivers State University, Port Harcourt, Rivers State, Nigeria

Keywords:

Framework, healthcare, management, NoSql, database, storage facility

Abstract

The tremendous adoption of new technology is responsible for the enormous volume of streaming data currently available. The traditional relational database paradigm faces many issues because of these enormous volumes of data. The primary concerns revolve around the efficiency of data retrieval and the database's ability to flexibly adjust its resources in response to changing requirements. However, because the new application architecture will be built on a NoSQL database, the adoption of NoSQL databases in new businesses is not a significant concern. However, a challenge arises when relational database-dependent systems that are already in place are redesigned to use NoSQL databases. To establish the fresh database structure, they need to review the system prerequisites once again. The goal of this project is to provide a framework for leveraging NoSQL databases to manage storage facilities for the healthcare industry. The notions of a relational structure (Table, Simple Attribute, Primary Key (PK), Foreign Key (FK), and Field List) and NoSQL concept (Document Collection, Document, Field, Embedded Field, ObjectId, DBRef) have been mapped conceptually. By creating object references between items that belong to documents, relationships were made possible. The metadata kept in the MySQL system tables was utilized by the mapping algorithm. PHP was used to implement the system. On the basis of migration speed and query speed, experiments on MySQL and MongoDB were carried out. Five queries were run to retrieve the number of rows from the product table to measure the read speed of each database. For each application, the average of these five requests was taken. MongoDB outperformed MySQL in a time comparison, clocking in at 1.78 sec versus 3.35 sec.

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Published

2023-09-20