Optimizing web application architectures for real-time data processing: insights from multi-industry projects

Joginpelly, Swarun Kumar (2025) Optimizing web application architectures for real-time data processing: insights from multi-industry projects. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 961-969. ISSN 2582-8266

Web application architectures optimized for real-time data processing have emerged as critical enablers for organizations seeking competitive advantage in data-intensive environments. Drawing from implementations across multiple industries, including the Polaris/Horizon insurance platform and Equipment Predisposed Tool for infrastructure management, four fundamental architectural pillars stand out: modular microservice architectures providing flexibility and targeted scaling; event-driven processing patterns minimizing latency while maintaining loose coupling; cloud-native technologies adapting to unpredictable workloads; and comprehensive security frameworks protecting data without compromising performance. These case studies demonstrate how organizations from diverse sectors have successfully implemented these architectural patterns to transform raw data streams into actionable insights, supporting critical business operations while meeting increasingly demanding performance requirements in environments where milliseconds often determine success or failure.