Architectural Deep Dive and Performance Evaluation: Scaling Relational Workloads with Amazon Aurora
Amazon Aurora, a cloud-native relational database engine, has emerged as a leading solution for scalable and high-performance database management. This paper explores Aurora’s unique architecture, focusing on its distributed storage system, adaptive scaling mechanisms, and high availability features. Through real-world case studies, we analyze how organizations have leveraged Aurora to enhance performance and scalability. Additionally, insights from prior benchmarking studies [21] provide an in-depth understanding of Aurora’s efficiency in handling dynamic workloads. This study provides insights into best practices for optimizing Aurora-based systems to achieve cost-efficient and resilient database solutions.
Authors
- rahul goel
Publication Details
- Journal
- International Journal For Multidisciplinary Research
- Published
- 2025-04-08
- DOI
- https://doi.org/10.36948/ijfmr.2025.v07i02.40977
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00