Databricks, an AI big-data company, announced a $5 billion funding round at a $190 billion valuation on Thursday after investors showed unexpected $15 billion in demand.
The company is cash-flow positive with $7 billion in annualized run-rate revenue growing at 80%, and has launched AI products including Lakebase (at $100M revenue run-rate) and Genie.
The capital will fund expensive AI research, multi-billion dollar cloud commitments with major hyperscalers, and ongoing acquisitions.
What happened
Databricks announced a $5 billion funding round at a $190 billion valuation on Thursday, led by Coatue with participation from Blackstone, MGX, T. Rowe Price accounts, and Sixth Street Growth. The round involved about two dozen VCs. CEO Ali Ghodsi said the company initially aimed to raise $1 billion but received $15 billion in interest from investors after The Information reported on the fundraise during the company's June conference.
Why it matters
Databricks has hit $7 billion in annualized run-rate revenue growing at 80% and is cash-flow positive, with its core cloud data warehouse product at $1.5 billion run-rate (growing 100% year-over-year) and newer AI product Lakebase already at $100M revenue run-rate. The company has multi-billion dollar cloud commitments with major hyperscalers and a 100-person AI research team, making sustained capital essential for AI infrastructure and M&A activity.
What to watch
Databricks has acquired Electric (PGlite's maker) this week, Panther (AI cybersecurity) in June, and two other startups in March, signaling continued acquisition pace. CEO Ghodsi told CNBC he still intends to take the company public eventually, though he says the focus for now is investing in AI rather than rushing to an IPO.
Databricks announced Thursday a $5 billion funding round at a $190 billion valuation, closing a round that began with far more modest ambitions. Co-founder and CEO Ali Ghodsi told TechCrunch the company originally intended to raise $1 billion but encountered an unexpected surge in investor demand after The Information published a report on the fundraise in June—timing that caught the company off guard as it was focused on running a conference. "As soon as that article went out, there was a long line of investors that started calling. My phone blew up. It was like the worst timing for us," Ghodsi recalled. The publicity turned into an enviable problem: among the investors the company actually engaged with, there was $15 billion of available interest to deploy. Facing pressure from long-term backers who wanted in, Databricks opted to expand the round and accommodate additional investors.
The $5 billion round closed in July at an initial $188 billion valuation before being officially announced Thursday at $190 billion. Coatue led the round, with participation from Blackstone, MGX, various T. Rowe Price accounts, and new investor Sixth Street Growth (the firm founded by former Goldman Sachs chief investment officer Alan Waxman). About two dozen VCs participated in total. The appetite for the deal reflects Databricks' strong operational performance and AI positioning. Ghodsi said the company has hit $7 billion in annualized run-rate revenue growing at 80% while remaining cash-flow positive. The core cloud data warehouse product—Databricks' original offering—is $1.5 billion of that run-rate and still growing 100% year-over-year. Newer AI products are scaling rapidly: Lakebase, a database for agents launched in June 2025, has already reached $100M revenue run-rate, and Genie, an AI chatbot tool for business analysis, is described as "insanely popular."
Despite already having raised $20 billion over the prior 20 months, Databricks is deploying the fresh capital against substantial structural costs. Ghodsi cited multi-billion dollar cloud commitments to all three major hyperscalers (Amazon, Microsoft, Google) and expensive AI research operations—the company maintains a 100-person AI research team in a highly competitive area. The company is also actively acquiring: this week it announced the purchase of Electric, maker of the lightweight Postgres database PGlite (useful for agents spinning up databases), and earlier acquisitions included AI cybersecurity company Panther in June and two other startups in March. When asked about going public, Ghodsi told CNBC he still wants to take Databricks public eventually, but for now prefers to focus on AI investment out of the public eye. With instant access to $15 billion in investor demand on his own terms, however, the pressure to rush is minimal.
Databricks' $5 billion raise exemplifies the dynamics of late-stage venture fundraising in the AI era. The company initially sought $1 billion—an amount that would have been considered a massive raise in earlier startup cycles—but public reporting about the round triggered a cascade of investor interest that transformed the deal. Ghodsi's account shows how information asymmetry in venture markets can create self-fulfilling prophecies: once The Information published the news during the company's June conference, the resulting investor inquiries made turning away capital providers diplomatically difficult, especially long-term backers. The result was a higher round size and valuation ($190 billion, up from $188 billion announced in July) to accommodate about two dozen VCs.
The strength of Databricks' underlying business justifies the investor enthusiasm. The company is cash-flow positive despite an $7 billion annual revenue run rate growing at 80%, a rare combination for high-growth AI infrastructure companies. Its core data warehouse product ($1.5 billion run-rate, growing 100% year-over-year) remains the anchor, but newer AI-focused offerings like Lakebase and Genie are scaling rapidly—Lakebase reached $100M revenue run-rate in its first months after launching in June 2025. However, the capital intensity of AI infrastructure is real: multi-billion dollar commitments to cloud hyperscalers and a competitive, expensive AI research function (100 employees) justify ongoing fundraising even at massive scale.
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