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Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · Lesson

Introduction to Kafka Streams

Get an overview of the Kafka Streams library, its purpose, and how it enables building continuous data processing applications.

Real-time Data: Stream Processing

Imagine data as a continuous flow, like a river. Stream processing is about analyzing and reacting to this data as it arrives, in real-time.

Unlike batch processing, which handles data in large, fixed groups (like a lake), stream processing works on individual data points or small windows of data as they are generated.

Meet Kafka Streams

Kafka Streams is a client library for building powerful stream processing applications. It's an integral part of the Apache Kafka ecosystem.

It allows you to process data stored in Kafka topics, perform transformations, aggregations, and then write the results back to Kafka or external systems.

All lessons in this course

  1. Introduction to Kafka Streams
  2. Stream Processing with KStream & KTable
  3. Building a Simple Stream Application
  4. Windowing and Stateful Aggregations in Kafka Streams
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