Tabular Acquisition Signals Multi Cloud Era

Databricks buying Tabular showed that open table formats had become too important to fight and had to be absorbed into the center of the platform battle. The strategic point was not just M&A. It was that Databricks, which had pushed its own Delta Lake format, now had to embrace Iceberg and interoperability because large enterprises increasingly run data across multiple clouds and engines. That shift helps dbt because the more storage formats standardize, the more value moves up into the workflow layer where teams define models, tests, metadata, and governance once.

• Before Iceberg, multi cloud usually meant copying the same data into multiple systems, which raised storage and compute costs and created sync errors. Once major data clouds publicly committed to a common table format in June 2024, multi cloud became something teams could actually operate, not just plan for.
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• For Databricks, Tabular was both defensive and offensive. Defensive because Iceberg threatened Delta Lake lock in. Offensive because owning the Tabular team and supporting Iceberg let Databricks sell itself as the place where Delta, Iceberg, governance, and AI workloads can all live together.
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• For dbt, the beneficiary is the layer above storage. dbt Core stays the place where teams write SQL models and business logic in an open framework, while dbt Cloud sells the browser IDE, scheduler, CI checks, docs, and governance that let many analysts and engineers collaborate across different warehouses without rewriting the same logic in each one.
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The next phase is a fight over who owns the control plane, not who owns a file format. As Iceberg and related interoperability features spread, storage becomes less of a moat and more of a shared substrate. That favors products like dbt that sit above the warehouse and make cross cloud workflows usable, governed, and repeatable across a fragmented data stack.