Real-time Data Integration: The Evolution of CDC Architecture

Abstract

This article explores the progression of Change Data Capture (CDC) methodologies, highlighting their transformation from periodic batch processes to instantaneous real-time frameworks. It examines Apache Hudi's architectural foundation for implementing efficient CDC solutions, emphasizing its complementary storage models and incremental processing functionalities. The article details stream processing enhancement techniques, including event-based architectures, distribution strategies, and flow control mechanisms that improve CDC workflow performance. Resource-efficient implementation patterns are discussed, contrasting utilization profiles across different CDC methodologies and storage approaches while addressing infrastructure scaling techniques. Performance measurement provides empirical data regarding response times, processing capacity, and resource consumption characteristics across diverse CDC implementations and operational scenarios, demonstrating the considerable advantages of contemporary CDC approaches over conventional synchronization methods.