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Principles in Data Stream Processing

Data stream processing is, for many of us, a new paradigm with which you process data and build applications. In this talk, we will take you on a journey through the theoretical foundations of stream processing and discuss the underlying principles and unique problems that need to be addressed. What actually is a data stream anyway? And how do I use it? How do streams relate to application state and when do I use the one or the other?

ksqlDB and Kafka Streams are both, at their core, designed to help build stream processing applications and we will explain how stream processing principles are reflected in the design of each system and what trade-offs were chosen (and - more importantly! - why). Finally, we take a look into the future how the stream processing space, and in particular ksqlDB and Kafka Streams, may evolve over the next few years as we outline extensions and improvements to the underlying conceptual model. So, bring your thinking hats and notepads and prepare to learn WHY these systems are the way they are!


Matthias J. Sax

Matthias is an Apache Kafka committer and PMC member, and works as a software engineer at Confluent. His focus is data stream processing in general, and thus he contributes to ksqlDB and Kafka Streams. Before joining Confluent, Matthias conducted research on distributed data stream processing systems at Humboldt-University of Berlin, were he received his Ph.D. Matthias is also a committer at Apache Flink and Apache Storm.

Nick Dearden

Nick Dearden is a technology and product leader at Confluent, where he enjoys leveraging many years of experience in the world of data and analytic systems to help design and explain the power of a streaming platform for every business. Prior to Confluent, he led the data platform group for a leading online real-estate seller and was chief architect for a cloud-based financial analytics platform. His early career stretches all the way back through multiple data warehouse and business intelligence adventures to the green-screen days of mainframe banking systems.