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I Thought Databricks Lakebase Wasn’t Groundbreaking — Then I Took a Closer Look
I’ll be honest — when I first saw the announcement for Databricks Lakebase, my reaction was: “Wait… haven’t we seen this before?”
Decoupled storage and compute?
Serverless architecture?
Zero ETL?
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These aren’t new ideas. AWS, Azure, and other cloud vendors have already rolled out similar capabilities. So what makes Lakebase different? Why all the buzz?
I wasn’t convinced — until I took a deeper look and realized something important. This isn’t just another serverless OLTP database. It’s a bridge between the operational and analytical worlds, fully integrated with the lakehouse we already love and use every day.
Let me walk you through how I changed my mind.
Feel free to skip this part: Are you trying to learn about data engineering with Databricks. I am offering a free webinar with live demo signup here
A Real Problem: Reverse ETL Overhead
In many of my Databricks-powered projects, we’ve built amazing pipelines — taking raw data, transforming it in the lakehouse, and delivering rich insights.
