Fabric Warehouse vs. Lakehouse: Same Storage, Different Engines

Fabric Warehouse vs. Lakehouse: Same Storage, Different Engines Episode 9 • 2026-02-27 Duration: 15:34 Matthias and Fabia dissect the Warehouse-vs-Lakehouse decision. They explore why three SQL options exist in Fabric, when the SQL endpoint's read-only design saves you, and why judging Warehouse performance on a cold-cache first query is the mistake everyone makes. What we discuss A real-world mistake from a pre-Fabric era The one question that reframes the architectural debate How we got here — predecessor products and evolution Why the "obvious" answer is often wrong A real Reddit/Microsoft Q&A question unpacked The concrete recommended architecture F-SKU realism — what this actually costs When the rejected approach is actually right Risks of the recommended path What Microsoft is shipping that changes the calculus The architectural principle to take home Key takeaways Today's takeaway. Warehouse and Lakehouse aren't competing products. They're different engines on the same storage. Pick based on workload pattern — T-SQL, multi-table transactions, auto-optimization means Warehouse. Spark, ML,... Fair. And honestly, for a lot of teams that works. If your reporting is read-only — dashboards, DirectLake — the SQL endpoint handles it fine. In a team of eight under cost pressure, Lakehouse plus SQL endpoint might be all you need. The... Right. So here's where people get it wrong. The naive answer is — Warehouse is for SQL people, Lakehouse is for Spark people. Pick your tribe. But that's way too simple. The real difference isn't the language you write. It's who owns the... Resources Warehouse in Fabric Create Warehouse T-SQL surface area Performance Guidelines Better together: Lakehouse and Warehouse Decision Guide: Warehouse vs Lakehouse SQL Analytics Endpoint Performance Result Set Caching Data Clustering Zero-Copy Table Clone Time Travel Transactions Migration from Synapse Architecture Warehouse Team AMA (March 2025) About the show Built on ElevenLabs voice synthesis. Matthias — cloned voice. Fabia — designed AI co-host. See Matthias live on YouTube (Fabric Friday), at his meetups, and at conferences like FabCon. Hosted by Matthias Falland — Microsoft Data Platform MVP and community architect behind the Fabric Periodic Table. New episodes every Friday. Submit your case Have an architecture decision you are wrestling with? DM Matthias on LinkedIn — find him as Matthias Falland. Three to five sentences about the decision, your team size, and your current stack. We anonymize before airing. Built on ElevenLabs voice synthesis. Brand design based on fabricperiodictable.com.