Get that Databricks Out of My Face!

Martyn Rhisiart Jones

Madrid, Monday 9th February 2026

You need not loathe Databricks outright. It is perfectly defensible if you do. This is particularly true when your principal objective is classical data warehousing. This includes structured BI reporting, dependable SQL analytics, and a governed single source of truth for business metrics. It also entails semantic clarity and predictable costs for read-heavy workloads.

There are solid, well-trodden reasons for that caveat. Many experienced data warehousing practitioners see Databricks as an awkward or even risky primary platform for traditional warehousing. This view is shared by some of the field’s foundational figures. The concern is not ideological. It is architectural. When used as a warehouse, Databricks often reproduces exactly the pathologies criticised in enterprise data programs. These include unnecessary complexity, misdirected effort, and the perennial executive question, “Which number should I trust?”

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