Performance Optimization of SQL Queries in Distributed Cloud Environments

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Anas Raheem

Abstract

As data-driven applications grow in scale and complexity, optimizing the performance of SQL queries in distributed cloud environments has become a critical concern. Cloud infrastructures offer elastic scalability and high availability, but these advantages often introduce new performance bottlenecks, especially when dealing with distributed databases, network latency, and query parallelization. SQL, as a declarative query language, relies heavily on underlying execution engines, which can vary significantly in behavior and efficiency across cloud platforms. This paper explores advanced strategies and best practices for optimizing SQL queries in distributed settings. It examines query design techniques, indexing strategies, data partitioning, caching mechanisms, and cost-based optimization. The paper also analyzes how cloud-native services and architectures—such as distributed SQL engines, serverless databases, and data warehouses—affect query performance. The goal is to provide a comprehensive guide to maximizing SQL efficiency in cloud environments by balancing execution speed, resource utilization, and system scalability.

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How to Cite
Anas Raheem. (2025). Performance Optimization of SQL Queries in Distributed Cloud Environments. Pioneer Research Journal of Computing Science, 2(2), 144–153. Retrieved from http://prjcs.com/index.php/prjcs/article/view/78

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