Optimizing NoSQL Database Performance: Elevating API Responsiveness in High-Throughput Environments

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Published: Jun 8, 2023

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Gopichand Vemulapalli

Abstract

In high-throughput environments, where APIs powered by NoSQL databases play a crucial role, ensuring optimal responsiveness is paramount for seamless user experiences. This paper explores performance strategies tailored to enhance API responsiveness when leveraging NoSQL databases. It examines the unique characteristics of NoSQL databases, their advantages in handling large data volumes, and challenges in maintaining responsiveness under heavy workloads. Strategies for optimizing API performance delve into architectural considerations, database tuning techniques, and effective caching mechanisms. Architectural considerations include scalable database sharding and asynchronous processing for long-running tasks. Database tuning techniques focus on indexing, query optimization, and scaling strategies. Effective caching mechanisms, such as in-memory caching with Redis and Content Delivery Networks (CDNs), are also discussed. Real-world case studies highlight successful implementations, including Twitter's scalability initiatives and Airbnb's API responsiveness enhancements through caching. In conclusion, proactive performance optimization is essential for delivering responsive APIs in high-throughput environments, leveraging NoSQL databases effectively to meet evolving data challenges.

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How to Cite
Optimizing NoSQL Database Performance: Elevating API Responsiveness in High-Throughput Environments. (2023). International Machine Learning Journal and Computer Engineering, 6(6), 1-14. https://mljce.in/index.php/Imljce/article/view/31
Issue
Vol. 6 No. 6 (2023): IMLJCE
Section
Articles

How to Cite

Optimizing NoSQL Database Performance: Elevating API Responsiveness in High-Throughput Environments. (2023). International Machine Learning Journal and Computer Engineering, 6(6), 1-14. https://mljce.in/index.php/Imljce/article/view/31

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