Bir, Jasvir and Sharma, Priynka and Prakash, Surya (2024) Experimental Evaluation of Scalable Database Architectures for High-Performance Applications. In: Computing and Machine Learning. Lecture Notes in Networks and Systems, 856 . Springer Nature, Singapore, pp. 31-46. ISBN 978-981-97-7570-5
Full text not available from this repository.Abstract
Choosing a database architecture significantly impacts scalability and high performance in data-intensive applications. This paper reports the results of our experiential evaluation of two prominent database architecture types using Oracle Hypervisor for prototyping. Our comprehensive experiments evaluated performance and involved configuring DHCP failover services with load balancing and an overarching clustering approach to establish a high-availability, fault-tolerant system. These experiments unveiled each architecture's performance strengths and weaknesses within the context of high-performance applications. Additionally, we explored the impact of increasing data volume, concurrent users, and complex queries on database performance, offering valuable insights into scalability and resilience under growing data demands and complex query workloads. This research contributes to the ongoing discourse on selecting databases for high-performance applications, providing practical insights that guide architects and developers in choosing the most suitable database architecture for contemporary data-driven applications.
| Item Type: | Book Chapter |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | School of Information Technology, Engineering, Mathematics and Physics (STEMP) |
| Depositing User: | Priynka Sharma |
| Date Deposited: | 08 May 2025 03:18 |
| Last Modified: | 08 May 2025 03:18 |
| URI: | https://repository.usp.ac.fj/id/eprint/14905 |
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