The Changing Face of ETL: Event-Driven Architectures for Data Engineers

A presentation at Confluent VUG by Robin Moffatt

Data integration in architectures built on static, update-in-place datastores inevitably end up with pathologically high degrees of coupling and poor scalability. This has been the standard practice for decades, as we attempt to build data pipelines on top of databases that do a poor job modelling the fundamental objects that drive our businesses and systems: events.

Events carry both notification and state, and form a powerful primitive on which to build systems for developers and data engineers alike. Developers benefit from the asynchronous communication that events enable between services, and data engineers benefit from the integration capabilities. Everyone gains from using the standards-based, scalable and resilient streaming platform.

In this talk, we’ll discuss the concepts of events, their relevance to both software engineers and data engineers and their ability to unify architectures in a powerful way. We’ll see how stream processing makes sense in both a microservices and ETL environment, and why analytics, data integration and ETL fit naturally into a streaming world. The talk will conclude with a hands-on demonstration of these concepts in practice using Apache Kafka and commentary on the design choices made.

Join this talk to learn:

  • The power of events and unbounded data
  • Streaming is not just for real-time applications—it’s for everyone
  • Where a streaming platform fits in an analytic architecture
  • How event-driven architectures can enable greater scalability and flexibility of systems both now and in the future


The following resources were mentioned during the presentation or are useful additional information.

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