Databricks Reaches $38 Billion Valuation After New $1.6 Billion Injection

AI-powered data company Databricks has raised its second billion-dollar funding round of the year, vaulting its valuation by $10 billion.

The San Francisco-based startup announced on Tuesday that it had raised $1.6 billion at a valuation of $38 billion in a Series H round led by Morgan Stanley. Baillie Gifford, ClearBridge Investments and the University of California’s investment office round out the new backers. “In some sense, we’re going public six months at a time,” says cofounder and CEO Ali Ghodsi, alluding to Databricks’ recent courtship with large fund managers, which more often put money into public companies than startups. In February, it raised $1 billion from non-venture capital investors including Franklin Templeton and Fidelity. Ghodsi, who told Forbes earlier this year that Databricks is IPO-ready, says the new financing does not impact its time line to go public, though he declined to share further details on the schedule.

Discussions about the new funding were first reported by Bloomberg earlier this month. Forbes estimate Ghodsi is now worth $1.8 billion and two cofounders, executive chairman Ion Stoica and chief technologist Matei Zaharia, are also billionaires based on their stakes in the company.

With the new financing, Databricks, which ranks No. 2 on Forbes’ 2021 Cloud 100 list, will beef up its data “lakehouse” software by adding new security and governance features, Ghodsi says. Databricks plans to have more than 3,000 employees by the end of the year—meaning a spree of 700 new hires in the next four months—to double down on sales, marketing and research and development efforts, he says.

The lakehouse combines elements of data warehouses (costly structured data used for analytics) with data lakes (cheap, raw data repositories). Databricks has a head start on the space, thanks to the background of its founders, seven University of California at Berkeley researchers who created Spark, the predictive data processing tool at the core of Databricks’ artificial intelligence software that harnesses data in the cloud to forecast predictions and discover insights about a company’s business. Oil giant Shell uses the software to predict when its oil rigs are likely to break, while pharmaceutical firm AstraZeneca uses it as a recommendation system to help scientists choose the best target sites for potential drugs.

MORE FROM FORBESAccidental Billionaires: How Seven Academics Who Didn’t Want To Make A Cent Are Now Worth BillionsBy Kenrick Cai

Ghodsi speaks with a newfound confidence that Databricks has established the lakehouse as a category, pointing to widespread use of the term by cloud giants like Amazon and growing startups like Fivetran and Dremio, the latter of which now markets itself on its website as a “lakehouse platform.” The market has exploded in the past six to seven months, he says, with more firms outside Silicon Valley such as AT&T and McDonald’s adopting the approach. The company’s annual recurring revenue is now more than $600 million, Ghodsi says, up from $425 million at the time of its previous funding round only seven months ago. He says Databricks is growing at a 75% annual rate, with its European business more than doubling this year.

To further its international reach, Databricks also announced it had hired longtime Salesforce executive Andy Kofoid, who most recently served as the software giant’s president of North American operations. The hire follows that of Fermin Serna as chief security officer earlier this month, signaling an executive team buildout commonly seen at startups gearing up for a public listing. Kofoid will become president of global field operations at Databricks. “He just ran an over $10 billion-a-year business, so he’s used to that massive scale, which we think we’ll see in the not-too-distant future,” says Ghodsi, who compares his company’s position to that of Salesforce two decades ago, when it effectively created the now ubiquitous software-as-a-service category.

To reach such a $10 billion revenue target will require Databricks to not only maintain its pole position among lakehouse vendors, but also to prevail against alternative data solutions, such as cloud data warehouses offered by competitors like Snowflake. “There’s this big data warehouse category, and I think they see the writing on the wall that this lakehouse category will probably replace the data warehouses, and they probably won’t be around a decade from now,” Ghodsi says. Snowflake, meanwhile, is expanding its own artificial intelligence tools in a bid to broaden its addressable market.

Ghodsi says he is not worried about on-premises data center providers such as Cisco and Dell, which may regain ground as enterprises become anxious about rising cloud costs. He doesn’t expect to see a large-scale shift away from the cloud: “That would be multiple steps back in terms of innovation.” Instead, he thinks companies will negotiate cloud providers including Amazon Web Services, Microsoft Azure and Google Cloud against each other. Companies like Databricks and Snowflake, he says, stand to benefit because their software works on any cloud platform, giving enterprises flexibility to jump between vendors.

Databricks is moving full speed ahead with its early bets on AI and an exclusive focus on the cloud. Both decisions have paid off as the pandemic boosted digital transformation across enterprises. “There’s an acceleration of the future that happened,” Ghodsi says. “Things are going to be automated, there’s going to be a lot of machine learning involved.” The enthusiasm from customers is perhaps matched only by investors. Ghodsi says Databricks could have increased its valuation well above $38 billion, but opted to “leave a little bit of money on the table” to boost potential returns for its new investors, who are likely to be long-term partners. “Frankly, it doesn’t cost us that much,” Ghodsi says.