In this chapter, we started with a detailed understanding of real-time stream processing concepts, including data stream, batch vs. real-time processing, CEP, low latency, continuous availability, horizontal scalability, storage, and so on. Later, we learned about Apache Kafka, which is a very important component of modern real-time stream data pipelines. The main features of Kafka are scalability, durability, reliability, and high throughput.
We also learned about Kafka Connect; its architecture, data flow, sources, and connectors. We studied case studies to design a data pipeline with Kafka Connect using file source, file Sink, JDBC source, and file Sink Connectors.
In the later sections, we learned about various open source real-time stream-processing frameworks, such as the Apache Storm framework. We have seen a few practical examples, as well. Apache Storm is distributed...
