HIGH-PERFORMANCE AT SCALE: UNDERSTANDING DATABASE AND CDN CACHING IN DISTRIBUTED SYSTEMS
Keywords:
Distributed Cache Systems, Edge Computing Optimization, Content Delivery Networks, Cache Coherency Protocols, Q-Learning Cache ManagementAbstract
This article presents a comprehensive analysis of modern distributed caching systems, focusing on Database Caching and Content Delivery Network (CDN) architectures. We examine how these systems handle unprecedented scalability challenges in today's digital landscape, where applications routinely process 150,000-200,000 requests per second. Through extensive research and production data analysis, article demonstrates that implementing distributed caching can reduce query latency by up to 83% while supporting a 6.5x increase in concurrent user load. The integration of edge computing with CDN architectures has shown remarkable improvements, processing an average of 325 TB of data per second and reducing content delivery latency by 81%. The article presents novel approaches to cache coherency, including directory-based protocols achieving 99.997% accuracy and Q-learning optimization techniques that improve cache hit ratios by 23.5%. Our findings demonstrate significant advancements in distributed caching technologies, particularly in areas of performance optimization, scalability, and real-world application across e-commerce, social media, and streaming platforms.
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