Databricks raises $5B at $134B valuation as AI revenue surges and IPO talk grows

Databricks just pulled in one of the largest private financings the data software sector has ever seen, locking up $5 billion in equity and another $2 billion in fresh debt capacity at a $134 billion valuation. The numbers land at a moment when public markets have offered few growth stories of this scale, and they arrive with a signal that Databricks is no longer thinking in quarters. It is thinking in eras.

The raise follows a $4 billion funding round completed in December at the same $134 billion valuation, underscoring how quickly investor demand accelerated into the new year.

The company said annualized revenue topped $5.4 billion in the January quarter, climbing 65% year over year and generating free cash flow over the past 12 months. That combination is rare among private software firms at this size. It reads less like a venture narrative and more like a public-market profile waiting for the right window.

Chief executive Ali Ghodsi framed the raise as optional rather than necessary. Interest surged over recent weeks, enough to push the round beyond early expectations. The company can stay private for as long as markets stay unsettled, he said, with enough cash on hand to avoid rushing an IPO. The message was clear. Databricks wants choice, not pressure.

“We’re seeing overwhelming investor interest in our next chapter as we go after two new markets,” said Ali Ghodsi, co-founder and CEO of Databricks. “With this new capital, we’ll double down on Lakebase so developers can create operational databases built for AI agents. At the same time, we’re investing in Genie to let every employee chat with their data, driving accurate and actionable insights.”

AI sits at the center of that confidence. Products tied to artificial intelligence now generate $1.4 billion in annualized revenue, according to the company. Customers use Databricks to connect enterprise data with AI models, deploy custom agents, and run analytics on top of massive datasets. Growth is speeding up, not slowing down. Just months ago, management was pointing to a 50% growth outlook. The latest figures move past that mark.

The timing matters. A new wave of high-profile listings may be forming for 2026. Fast-growing AI labs like Anthropic and OpenAI have been weighing public debuts, according to people familiar with the plans. SpaceX has surfaced in similar conversations after comments from Elon Musk late last year. Against that backdrop, Databricks looks less like a software vendor and more like infrastructure for the next phase of enterprise computing.

The latest funding brought in a familiar mix of Wall Street and long-term capital. Participants include Goldman Sachs, Glade Brook Capital, Morgan Stanley, Neuberger Berman, and the Qatar Investment Authority. JPMorgan led the debt facilities. With billions now sitting on the balance sheet, Databricks has room to fund product bets, acquisitions, and employee liquidity without trimming ambition.

The gap in scale with public peers keeps widening. Snowflake reported $1.21 billion in revenue for its October quarter and has a market cap of nearly $58 billion. Databricks now generates more revenue on a run-rate basis and is pushing into new territory. The wide release of its Lakebase database last week puts pressure on established vendors like Oracle and SAP, right as investors question the durability of traditional software moats.

That tension showed up in the market. Oracle and Snowflake shares both slid roughly 13% last week after concerns surfaced around open-source plugins tied to Anthropic’s Claude Cowork productivity tools. Ghodsi called the selloff an overreaction. The incumbents are not disappearing, he said, though their defenses are thinning.

Databricks now sits in a position few private companies reach. It has scale, cash flow, and a business tied directly to how enterprises plan to deploy AI at the production level. An IPO remains an option, not an obligation. For now, the company is content to keep building, flush with capital, and let the market come to it when it is ready.

Databricks Team