Real-Time Stream Processing of Big Data

The evolution of technology has enabled the continuous generation of massive data from connected devices and sensors. As, more data becomes available, organizations are using cutting-edge tools and techniques to extract useful insight from the data immediately they are generated. Therefore, the enterprise systems are evolving and shifting towards real-time systems. So, there is a growing need for well-developed fault tolerant distributed scalable systems to handle this change with low latency. Recent years have seen the emergence of several distributed systems whose popularity is as a result of the growing demand to efficiently analyze and interpret voluminous data. This article will discuss distributed real-time stream processing of big data, the two main real-time big data processing architectures: Lambda and Kappa and the popular frameworks used for processing real time big data.