Optimizing Kafka Streams Joins for Business-Critical Processes

In this session, we will delve into the practical boundaries of the Kafka Streams DSL and showcase why the Processor API stands out as the ultimate tool for addressing complex streaming scenarios. Using Michelin’s tire delivery process as a guiding example, we will illustrate how the different join types can be implemented with the DSL and where its limitations begin to emerge.

The challenges of joining events from multiple topics, whether driven by event-based or time-based logic, and achieving fine-grained control over state stores led us to embrace the Processor API. While the DSL is convenient and expressive for many use cases, the Processor API consistently proves to be the most powerful solution for real-world applications requiring precision and flexibility.

Whether you’re an architect, developer, or Kafka enthusiast, this session will equip you with actionable insights into designing custom state stores, optimizing for low latency, and implementing adaptable join logic to meet evolving business needs. Rather than advocating for abandoning the DSL entirely, the session highlights the importance of recognizing its limitations and understanding why the Processor API is often worth the additional effort.