Episode description

Do you ever feel like you’re short on time? Well, good news! Confluent Software Engineer Matthias J. Sax is back to discuss how event streaming has changed the game, making time management more simple yet efficient. 

Matthias explains what watermarking is, the reasons behind why Kafka Streams doesn’t use them, and an alternative approach to watermarking informally called the “slack time approach.” 

Later, Matthias discusses how you can compare “stream time,” which is the maximum timestamp observed, to the watermark approach as a high-time watermark. Stick around for the end of the episode, where Matthias reveals other new approaches in the pipeline. Learn how to get the most out of your time on today’s episode of Streaming Audio!

EPISODE LINKS

• Kafka Summit talk: The Flux Capacitor of Kafka Streams and ksqlDB
• Watermarks, Tables, Event Time, and the Dataflow Model
• Kafka Streams’ Take on Watermarks and Triggers
• Join the Confluent Community Slack
• Learn more with Kafka tutorials, resources, and guides at Confluent Developer
• Live demo: Kafka streaming in 10 minutes on Confluent Cloud
• Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)