Databricks and Microsoft partnership expands Azure AI strategy

The Databricks and Microsoft partnership is entering a new phase, with the two companies extending their decade-long strategic relationship into the 2030s. The expanded collaboration will see Databricks deepen its use of Azure Databricks for core business operations and its unified lakehouse, while increasing its use of Microsoft’s Azure Cobalt infrastructure.

At the same time, Microsoft will continue integrating the Databricks Data and AI platform across its product ecosystem. The broader aim is to help enterprises build AI that can work with their own business data and context while giving them more control over governance, costs and deployment.

Databricks puts Azure Databricks at its core

A key part of the agreement is Databricks' decision to run its own core business operations and analytics on Azure Databricks. This means the company will use the same platform it provides to customers for running critical workloads at enterprise scale.

The move also strengthens the role of Azure Databricks in the wider partnership. For enterprise customers, the focus is on bringing data, analytics and AI workloads into an environment that can support performance, security and scale.

Azure Cobalt targets performance and efficiency

Databricks will expand its use of Azure Cobalt, Microsoft’s Arm-based infrastructure, for agentic and data-intensive workloads. The company currently uses Cobalt 100 and plans to adopt Cobalt 200, which offers up to 50% better performance and has memory encryption enabled by default.

The infrastructure push is important as enterprises look to scale AI workloads without allowing performance and infrastructure costs to grow unchecked. The partnership is therefore linking AI capabilities with the underlying infrastructure needed to run them efficiently.

Genie and Unity AI Gateway move deeper into Microsoft

The partnership is also expanding around Databricks Genie AI co-worker and Unity AI Gateway. Genie and Genie Ontology are designed to help ground AI agents in enterprise data and business knowledge, while Unity AI Gateway provides governance for models, agents and costs.

These capabilities are being integrated across Microsoft's broader ecosystem, including Microsoft Entra, Azure Data Lake Storage, Microsoft OneLake, Power BI, Microsoft Purview, Microsoft Foundry, Power Platform, Microsoft 365, Teams and Copilot.

The direction is clear. Instead of treating AI as a separate layer, the companies are working to connect data, AI and business workflows. This could help enterprises build AI systems that have access to more relevant business context while maintaining control over how models and agents are governed.

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