Apache Kafka - Real-time Stream Processing (Master Class) - Real-time Streaming Design Consideration

The lecture discusses the importance of data integration in enterprises, emphasizing the need for real-time data integration. It outlines five critical decision criteria: time sensitivity, decoupling, data format, reliability, and scalability. The lecture evaluates four data integration patterns: shared database, remote procedure invocation, file transfer, and messaging, highlighting the advantages of pub/sub messaging. Apache Kafka is introduced as a robust pub/sub system that meets all criteria, offering a scalable and reliable solution for real-time data streaming.

Describe the four main patterns of integrating applications for data exchange.

What are the limitations of using a shared database for data integration?

Explain the role of the broker in a pub-sub messaging system.

How does Apache Kafka address the requirements for real-time data integration?