Streaming Engines
Last Updated: February 3, 2026
Throughout this section, we have discussed stream processing as a concept. We have seen it as the speed layer in Lambda Architecture and as the sole processing paradigm in Kappa Architecture.
But how do streaming engines actually work? What makes them capable of processing millions of events per second while maintaining exactly-once semantics?
What are Streaming Engines?
Streaming engines are complex distributed systems that handle continuous data flows. They must maintain state across events, handle failures gracefully, and provide the primitives for building real-time applications. Understanding how they work helps you choose the right engine and use it effectively.
In this chapter, you will learn:
- Core concepts that all streaming engines share
- How popular engines (Flink, Kafka Streams, Spark Streaming) work
- State management and checkpointing mechanisms
- Processing guarantees and exactly-once semantics
- How to choose the right streaming engine for your use case