One of the most interesting shifts in the Databricks ecosystem is Lakebase.
For years, data architectures have enforced clear boundaries:
OLTP → Operational databases
OLAP → Analytical platforms
ETL → Bridging the gap
While familiar, this model often creates complexity driven more by system separation than by business needs.
Lakebase introduces a PostgreSQL-compatible operational database natively integrated with the Lakehouse — and that has meaningful architectural implications.
Less data movement
Fewer replication patterns
More consistent governance
Operational + analytical workloads closer together
What I find compelling is the mindset shift:
We move from integrating systems
to designing unified data ecosystems.
From a presales perspective, this changes the conversation from:
“Where should data live?”
to
“How should data be used?”
Personally, this feels like a very natural evolution of the Lakehouse vision.
