Streaming Queries: Enabling Real-Time Elastic Scaling in Modern Applications

Authors

  • Manas Sharma Google, USA

DOI:

https://doi.org/10.32996/jcsts.2025.7.3.36

Keywords:

Elastic Scaling, Stream Processing, Real-time Analytics, Resource Optimization, Fault Tolerance

Abstract

The evolution of streaming queries has revolutionized how organizations handle real-time data processing and elastic scaling in modern computing environments. The shift from traditional batch processing to streaming architectures addresses critical challenges in resource allocation, latency reduction, and system performance optimization. By enabling continuous data processing and immediate response capabilities, streaming queries have transformed how businesses manage dynamic workloads across content delivery, e-commerce, and transportation sectors. The integration of AI-driven optimization and structured streaming techniques has established new benchmarks in processing efficiency, resource utilization, and fault tolerance, fundamentally changing how organizations approach real-time data analytics and decision-making.

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Published

2025-05-03

Issue

Section

Research Article

How to Cite

Manas Sharma. (2025). Streaming Queries: Enabling Real-Time Elastic Scaling in Modern Applications. Journal of Computer Science and Technology Studies, 7(3), 319-326. https://doi.org/10.32996/jcsts.2025.7.3.36