Kafka's Role in Real-Time Data Processing within Hadoop
Kafka: The Powerhouse of Stream Processing within Hadoop The world of big data is constantly evolving, and with it, the need for efficient and scalable processing solutions. While Hadoop has long been the champion for batch processing, the advent of real-time applications demanded a new approach – one that could handle the continuous influx of streaming data. Enter Kafka, a distributed streaming platform that seamlessly integrates with Hadoop, forming a powerful duo for tackling both batch and real-time data challenges. Understanding Kafka's Strengths: At its core, Kafka is a highly scalable, fault-tolerant, and low-latency message broker. Imagine it as a vast pipeline, constantly moving streams of data across your infrastructure. This "publish-subscribe" system allows applications to send and receive messages...