Optimizing Data Storage and Retrieval in NoSQL Databases Strategies for Scalability

Abstract

This section of the paper draws upon real-world experiences from June 2020 to July 2022 at Bank of America, focusing on optimizing NoSQL databases to meet critical performance, scalability, and reliability needs in financial services. Facing challenges such as the management of diverse data types and ensuring high system availability, strategic methodologies were employed, including advanced data modeling, schema design adjustments, and storage optimization techniques like sharding and partitioning. These efforts were aimed at improving query performance, enhancing scalability, and ensuring data availability for crucial banking operations, including transaction processing and fraud detection. It delves into the intricacies of optimizing data storage and retrieval processes in NoSQL databases, addressing the challenges and complexities inherent in managing diverse data types and high scalability requirements. It explores best practices and strategies for designing efficient data models, implementing storage optimization techniques, enhancing query performance, and leveraging caching and memory management mechanisms. Real-world case studies and examples illustrate successful optimization efforts, while discussions on emerging trends and future directions offer insights into the evolving landscape of NoSQL database optimization.