Databricks did not set out to make its latest financing round quite this large. According to co-founder and CEO Ali Ghodsi, the AI big-data company wanted to raise $1 billion, but investor demand quickly changed the shape of the deal.
The result was a $5 billion round at a $190 billion valuation, announced Thursday, after interest from investors reached $15 billion among the group Databricks considered.
How a $1 Billion Plan Became a $5 Billion Round
Ghodsi told TechCrunch that Databricks was not focused on fundraising when The Information published an article saying the company was working on a major raise. The timing, he said, collided with a Databricks conference that took place in June.
Once the article appeared, investors began calling. Ghodsi described the response as immediate and intense, saying his phone filled with inbound interest while the company was busy with its conference.
That demand created a familiar problem for high-profile late-stage startups. When many existing and prospective backers want into a round, turning away long-term investors can create friction. Databricks chose to sell more shares than it initially planned.
In July, the company announced a new round at a $188 billion valuation, but it did not say at the time how much money it had raised. On Thursday, Databricks said the round totaled $5 billion and that its valuation had moved up to $190 billion.
Who Joined the Databricks Funding Round
The $5 billion Databricks funding round was led by Coatue and several others. The investor list included Blackstone, MGX, various accounts associated with various arms of T. Rowe Price, and new investor Sixth Street Growth.
Sixth Street Growth is part of the firm founded by former Goldman Sachs chief investment officer Alan Waxman. In all, about two dozen VCs were named as participants in the deal.
The size of the raise shows how strongly investors are still chasing private AI infrastructure and data companies. It also shows how Databricks can use investor demand to stay private while still accessing very large amounts of capital.
For a company with a broad roster of backers, a private round can also help manage expectations among investors who want exposure before a public offering. But it can make the eventual path to liquidity more complicated, since many investors will eventually expect a way to cash out.
Why Investors Were So Interested
Ghodsi said Databricks has reached $7 billion of annualized run rate revenue. He also said that revenue is growing at 80% and that the company is cash-flow positive.
The company’s core product, a cloud data warehouse, accounts for $1.5 billion of that run-rate, according to Ghodsi. He said that business is still growing at 100% year-over-year.
Databricks also has newer AI products that appear to be drawing attention. Lakebase, described as a database for agents, launched in June, 2025 and has reached a $100M revenue run-rate. Genie, the company’s AI chatbot tool for business analysis, was described by Ghodsi as “is insanely popular.”
Those figures help explain why investors were willing to push into a round that began with a much smaller target. Databricks sits at the intersection of data infrastructure, cloud computing and AI, areas where customers are spending heavily and where investors expect large markets.
Why Raise More When Databricks Already Raised $20 Billion?
The company had already raised $20 billion over the past 20 months, but Ghodsi said AI remains expensive. Databricks has multi-billion dollar cloud commitments with all three of the major hyperscalers.
Research is another cost center. Ghodsi said the company has an AI research team of 100 people, and described the field as highly competitive.
Databricks is also using capital for acquisitions. Ghodsi said, “We do a lot of M&A.” This week, the company announced the acquisition of Electric, which makes the lightweight Postgres database PGlite. The source described PGlite as a way for agents to spin up databases, and said the terms were undisclosed.
That deal followed other recent acquisitions. In June, Databricks bought AI cybersecurity company Panther. In March, it bought two startups.
Taken together, the spending profile is clear:
- Large cloud commitments tied to AI demand.
- A sizable internal AI research team.
- Continued M&A across data, security and agent infrastructure.
- Rapid growth in both core data warehousing and newer AI products.
The Public Offering Question Is Still Open
Databricks’ repeated private fundraising has become a running topic in Silicon Valley. When the latest round was announced last month, people joked online that the company had raised so many rounds it was running out of letters of the alphabet.
Ghodsi told CNBC that he still wants to take the company public one day. That remains an important point because Databricks now has a large investor base, and those investors will eventually want liquidity.
For now, the company appears to be prioritizing investment over a public market debut. With AI costs rising, cloud commitments in place and acquisitions continuing, staying private gives Databricks room to spend without the same level of public-market scrutiny.
The bigger point is that Databricks did not merely raise because it needed access to capital. It raised because investor demand made a larger private round available on attractive terms. When a company can draw $15 billion of interest and choose to take $5 billion at a $190 billion valuation, the urgency to go public becomes less obvious.