Abstract :

The Need To Have More Flexible, Scalable, And Costefficient Data Management Systems Over Traditional Database Systems Has Been Discussed In This Research. This Paper Examines The Benefits Of Amazon Web Services (AWS) Relational, Data Warehouse, And NoSQL Databases Compared To Traditional Methods. The Methodology Employed In Conducting The Study Was Based On A Secondary Qualitative Approach And Guided By An Interpretivistic Philosophy And An Inductive Approach. A Thematic Analysis Of Peer-reviewed Articles Identified In Google Scholar, IEEE Xplore, ScienceDirect, And SpringerLink Databases Is Used As The Research Source Of Data. The Analysis Has Provided Valuable Insights That Specifically Give Three Major Themes In The Database System Of AWS. The Title Of The First Theme, Overcoming Limitations Of Traditional Database Systems, Emphasises The Continual Inflexibility, High Cost, And Low Scalability Of Traditional Systems That Are Dealt With In AWS Solutions. All Three Products, Such As Amazon Aurora, Redshift, And DynamoDB, Provide Elasticity, High Availability, And Scaling To The Data Requirements Of The Present Day. The Second Aspect, Comparative Features And Performance Of AWS Databases, Shows That The Two DB Types, Such As Data Warehouse And NoSQL Databases, Have Identical Purposes And Cannot Be Considered Complementary To Each Other. Collectively, They Can Facilitate Hybrid Ecosystems, Which Are Transactional, Analytical, And Unstructured Workloads, And Can Be Supported By Their Usual Systems. The Third Theme, Advantages In Scalability, Cost Efficiency, And Integration, Shows That AWS Databases Not Only Increase Dynamically And Decrease Costs On Infrastructure, But Also Are Integrated With More Sophisticated Services. These Services Include Analytics, Machine Learning, Realtime Processing, And More. The Findings Establish That AWS Databases Deliver Interconnected Benefits, Creating Transformative Value For Organisations Navigating Data-driven Environments. The St

Published:

06-1-2024

Issue:

Vol. 24 No. 1 (2024)

Page Nos:

158-165

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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