I believe that architectures centered around real-time event streams and stream processing will become ubiquitous in the years ahead. Technically sophisticated companies like Netflix, Uber, Goldman Sachs, Bloomberg, and others have built out this type of large, event-streaming platform operating at massive scale. It’s a bold claim, but I think the emergence of stream processing and the event-driven architecture will have as big an impact on how companies make use of data as relational databases did.
Event thinking and building event-driven applications oriented around stream processing require a mind shift if you are coming from the world of request/response–style applications and relational databases. That’s where Kafka Streams in Action comes in.
Stream processing entails a fundamental move away from command thinking toward event thinking—a change that enables responsive, event-driven, extensible, flexible, real-time applications. In business, event thinking opens organizations to real-time, context-sensitive decision making and operations. In technology, event thinking can produce more autonomous and decoupled software applications and, consequently, elastically scalable and extensible systems.