Databricks raises $5 billion at $190 billion valuation as revenue run rate tops $7 billion

Databricks has closed a $5 billion funding round at a $190 billion valuation, giving the data and AI company another massive pool of private capital as enterprise spending on AI agents pushes its revenue higher.

The financing comes less than a month after Databricks raised new funding at a $188 billion valuation, and just six months after it secured $5 billion in equity financing plus $2 billion in debt capacity at a $134 billion valuation. The pace says plenty about investor appetite for one of Silicon Valley’s most valuable private companies.

Databricks said Thursday that its revenue run rate has crossed $7 billion, with revenue growing more than 80% year over year in its second quarter. CEO Ali Ghodsi summed up what the company is seeing from customers in three words during an interview with CNBC’s Jon Fortt: “demand is crazy.”

“What’s happening basically is everybody’s using these agents, AI agents, and the whole world is laser focused on agents, AI, and sort of you know that core part of it,” Ghodsi told  CNBC.

Coatue, Blackstone, MGX, T. Rowe Price and Sixth Street Growth led the new round. Databricks said it plans to use the capital to invest in its enterprise AI business, in which companies are spending heavily to connect AI models and agents to their corporate data.

AI agents are turning into a major business for Databricks

Founded in 2013 by Ghodsi and fellow researchers from the University of California, Berkeley, Databricks emerged from the team behind Apache Spark. It has since grown from a data analytics company into a broader enterprise AI platform with roughly 8,000 employees.

That shift is showing up in its newer products.

Lakebase, the company’s database built for AI agents, has already crossed a $100 million revenue run rate. Its Lakehouse data warehousing business has passed a $1.5 billion run rate. Ghodsi cited growing demand for Genie, its business-focused AI agent, and AI Gateway, which gives companies a way to manage which AI models employees and applications use and track the associated costs.

The cost piece is becoming particularly significant.

Companies racing to deploy AI agents can generate enormous volumes of tokens, turning model usage from an experimental expense into something CFOs are watching closely. Ghodsi said that shift is changing how businesses think about proprietary and open-source models, including models developed in China.

“The attitude a year or two ago was we just need frontier proprietary, and we can just ignore Chinese models,” he said. “What has happened is that this token maxing has freaked out the CFOs.”

That creates an interesting opening for Databricks. The company does not need one AI model to win. It can benefit from companies using multiple models and seeking infrastructure that helps control access, data, and spending across them.

Databricks: A $190 billion company that isn’t rushing to Wall Street

Databricks has now surpassed publicly traded rival Snowflake in market value, at least based on its latest private valuation. Yet Ghodsi appears in no hurry to test that valuation on the public markets.

The company has long been viewed as one of Silicon Valley’s biggest IPO candidates. The question has increasingly shifted from whether Databricks will go public to when.

SpaceX’s blockbuster IPO helped reopen the door to major technology listings, though volatile trading since its debut has served as a reminder that public investors can be far less forgiving than private-market backers. OpenAI and Anthropic have both confidentially filed for IPOs and could enter the public markets as soon as this year.

Databricks is taking a different route for now.

“We’re not just a company that wants to stay in the private, but right now I just think there would be too much distraction in the public market,” Ghodsi said.

At $190 billion, Databricks has the luxury of waiting. Private investors are still willing to write multibillion-dollar checks, revenue is climbing, and AI agents are creating new demand for the data infrastructure sitting underneath them.

The bigger test will be whether Databricks can turn that demand into growth that eventually supports its extraordinary private valuation in public markets. For now, investors appear willing to give Ghodsi more money and more time to find out.

Databricks Team