So you've embraced Apache Kafka as the core of your data infrastructure, embracing event-driven services that communicate with each through topics, integrate with legacy systems through an ecosystem of connectors, and respond more or less in real time to things that happen in the world outside your software. Logs of immutable events form a more robust backbone than the one-database-to-rule-them-all of your deep monolith past. Your stack is more evolvable, more responsive, and easier to reason about. There's just one problem: now that everything is a stream, how do you query things?
If this is you, you can probably name at least one or two ways off the top of your head, but have you stopped to think through how to make the choice? It is time you did. In this talk, we'll explore the solutions currently in use in the world for asking questions about the contents of a topic, including Kafka Streams, the various streaming SQL implementations, your favorite relational database, your favorite data lake, and real-time analytics databases like Apache Pinot. There is no single correct answer to the question, so as responsible builders of systems, we must understand our options and the tradeoffs they present to us. You'll leave this talk even happier that you've embraced Kafka as the heart of your system, and ready to deploy the right choice for querying the logs that hold your data.