A stream processing system operates directly on continuously arriving data streams, allowing connected enterprise systems to evaluate and manipulate data in near real time. section 4.4
Typical stream-processing operations include:
- Filtering incoming data. section 4.4
- Manipulating individual data sets. section 4.4
- Joining or connecting different data streams. section 4.4
Kafka-based implementations include Kafka Streams, Apache Flink, and Scala’s Akka. Stream-processing libraries support scalable and robust processing on large data sets, while some commercial offerings avoid programming. section 4.4
Figure 4.12 Kafka alone is usually not enough. The Kafka ecosystem offers numerous components to integrate Kafka into our enterprise landscape and thus build a streaming platform.
Shows how stream processing fits within a broader Kafka streaming platform alongside enterprise integration components. section 4.4
