Databricks is deepening its reliance on Microsoft’s cloud infrastructure in a sweeping new deal that extends the companies’ strategic alliance into the 2030s, a move that locks in a key enterprise software partner for Azure while giving Databricks access to custom silicon designed for the next wave of artificial intelligence workloads.

The expanded partnership, announced Wednesday, will see the San Francisco-based data and AI powerhouse run more of its own core business operations on Azure Databricks and significantly increase its consumption of Azure Cobalt, Microsoft’s Arm-based custom processors. For Microsoft, the agreement represents a high-profile endorsement of its homegrown chip strategy at a moment when enterprise AI adoption is accelerating and cloud providers are racing to differentiate their infrastructure.

Databricks, which last week disclosed it had secured a funding round valuing the company at $188 billion, provides a unified platform that helps organizations ingest, analyze, and build AI applications using complex data from disparate sources. The company counts more than 20,000 organizations as customers, including 70 percent of the Fortune 500.

Under the new framework, Databricks will shift its own internal analytics and operational workloads onto Azure Databricks, effectively eating its own dog food on the platform it sells to enterprises. That commitment is paired with a hardware roadmap: Databricks already uses Cobalt 100 chips and plans to adopt the next-generation Cobalt 200, which Microsoft says delivers up to 50 percent better performance and includes memory encryption enabled by default.

“For nearly a decade, Databricks and Microsoft have helped enterprises innovate with data and AI,” said Ali Ghodsi, Co-Founder and CEO of Databricks. “Today, our partnership is stronger than ever. With Databricks Genie and Unity AI Gateway deeply integrated across Microsoft’s products, we’re helping enterprises unify their data and ground AI in business knowledge. This lets customers get the full benefits of agents and models while controlling costs and ensuring governance.”

Judson Althoff, CEO of Microsoft’s Commercial Business, framed the deal as a foundation for the coming generation of enterprise AI. “The next generation of AI will be defined by how effectively organizations turn their unique knowledge into intelligence,” Althoff said. “With Databricks deepening its investment in Azure Databricks and Azure Cobalt-powered infrastructure, customers will benefit from greater performance, efficiency, and scale for their most demanding workloads.”

Althoff added that Databricks’ decision to run its own core business operations on the Azure platform gives customers confidence in a system “proven at enterprise scale.”

Custom silicon takes center stage

The deal highlights how cloud providers are increasingly using custom chips to compete on both price and performance for AI workloads. By moving more workloads to Cobalt processors, Databricks is betting that Arm-based architecture can handle the data-intensive and agentic AI tasks that enterprises are now deploying. The shift also aligns with broader industry momentum away from sole reliance on traditional x86 server processors.

The integration goes well beyond infrastructure. Microsoft will continue weaving Databricks’ AI capabilities across its product ecosystem, including its conversational analytics tool Genie, which functions as an AI co-worker that can be embedded directly into customer workflows. The companies are also touting deep integration of Unity AI Gateway, which governs models, agents, and costs, across the Microsoft stack — spanning Microsoft Entra, Azure Data Lake Storage, Microsoft OneLake, Power BI, Microsoft Purview, Microsoft Foundry, Power Platform, Microsoft 365, Teams, and Copilot.

The result, the companies argue, is an environment where governed, real-time data and AI flow directly into business workflows, giving organizations the context, control, and cost efficiency to scale AI without losing control over sensitive information or ballooning cloud bills.

Enterprise momentum

The expanded alliance builds on a decade-long relationship and comes as enterprises wrestle with connecting AI to trusted business knowledge while governing models and agents consistently. Thousands of joint customers — including Banco Bradesco, the Cincinnati Reds, Electrolux, SMBC, and Unilever — already run critical workloads on Azure Databricks.

Databricks’ move to deepen its Azure commitment also signals how the cloud market is evolving. As enterprises shift from experimenting with AI to deploying it at scale, they are increasingly looking for integrated stacks that combine data platforms, AI tooling, and optimized infrastructure. The Microsoft-Databricks partnership positions Azure as a default destination for organizations that want to build AI grounded in their own business context rather than relying solely on generic large language models.

The funding round that values Databricks at $188 billion — expected to close later this summer — underscores the premium investors are placing on companies that sit at the intersection of data infrastructure and AI. The company has positioned its platform as a unified lakehouse architecture that handles everything from data engineering to machine learning to the deployment of AI agents, a breadth that competes with offerings from cloud-native rivals and established players alike.

For Microsoft, the extended partnership shores up Azure’s competitive position against Amazon Web Services and Google Cloud, both of which are also investing heavily in custom silicon and AI platform capabilities. Locking in a high-growth partner like Databricks through the 2030s provides a long-term anchor tenant for Azure’s custom chip program and reinforces the ecosystem around Microsoft’s enterprise AI vision.