Tableflow: Materialize Apache Kafka® Topics as Apache Iceberg™ and Delta Lake Tables With Zero ETL

Blog post: https://cnfl.io/4hNOPFn | Tim Berglund is back at the lightboard to show you the most exciting thing he’s seen in analytics in the last 40 years (nope, that’s not an exaggeration): Tableflow, a new feature in Confluent Cloud that lets you completely skip the ETL and make your Apache Kafka® topic data available as tables in your data lake.

In this video, Tim walks through how Tableflow works and why it’s a big deal—no data copying, no transformation steps, just native open table formats like Apache Iceberg™ and Delta Lake right on top of your Kafka data.

Along the way, he explains how we got here (Hint: It involves the evolution of the data warehouse and a copious amount of wrestling with schema and pipelines over the years) and how Tableflow bridges the gap between operational and analytical systems, eliminating unnecessary data movement. Tim also explains how Apache Flink® fits into the picture to help you clean and prep your data upstream.

If you’re working with Kafka and modern data lakes, this is one of those tools you’ll probably want to have in your back pocket.

RELATED RESOURCES
► Tableflow Announcement: https://cnfl.io/4hNOPFn
► Tableflow Product Page: https://cnfl.io/4iXBGe2
► Tableflow Feature Walkthrough: https://cnfl.io/423dEaR
► Try Confluent Cloud for Free: https://cnfl.io/440ZU2C

CHAPTERS
00:00 – Intro to Tableflow
00:35 – Data warehousing: The classical era
02:50 – The rise of distributed data lakes
05:00 – ELT vs. ETL and the return of schema
06:40 – Emergence of open table formats
08:00 – Decoupling storage and compute in the cloud
08:45 – How data enters the lake today (Kafka)
10:00 – The cost of data copying and context loss
11:20 – How Tableflowworks: Kafka topics as tables
13:05 – How Tableflow uses Schema Registry
14:00 – Shift data transformation and cleaning left with Flink
15:45 – Try Tableflow in Confluent Cloud for free

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