Databricks raises record $10 billion to fuel further growth
The data lakehouse pioneer has expanded into AI development and plans to use the funding to fuel further investments in AI, make acquisitions and expand go-to-market efforts.
Databricks on Tuesday unveiled that it is in the process of completing the largest funding round in history, raising $10 billion in venture capital.
To date, Databricks has completed $8.6 billion of the $10 billion, bringing its valuation to $62 billion, according to the vendor. At $10 billion, the vendor's Series J round would significantly exceed the $6.6 billion raised in September by OpenAI, which at the time was widely reported to be the largest single funding round in history.
Based in San Francisco, Databricks is a data management vendor that helped pioneer the development of the data lakehouse for cloud-based data storage, which combines the structured data storage capabilities of data warehouses with the unstructured capabilities of data lakes.
During the past two years, the vendor has expanded beyond data management into AI development, building an environment for customers to create their own models and applications.
With enterprises increasing their investments in developing generative AI, given its potential to transform businesses by making employees smarter and more efficient, investors have been attracted to tech companies whose tools enable AI development. In addition to OpenAI, the developer of ChatGPT, Anthropic -- which develops the Claude line of generative AI models -- also executed one of the largest funding rounds in history by raising $4 billion in March.
Meanwhile, given that data platform vendors such as Databricks and Snowflake are venturing into AI development, investors view them similar to pure AI vendors, according to David Menninger, an analyst at ISG's Ventana Research.
Databricks, however, has separated itself from many competitors with the speed, depth and breadth of its AI development capabilities, including its own large language model (LLM). As a result, it's been able to attract huge amounts of funding.
Databricks is one of the few data platform vendors that has ventured into creating their own LLMs. This may give them the opportunity to own more of the AI stack than other data platform providers. They have also done a very good job developing an ecosystem around their platform that provides fertile ground … to expand product capabilities and revenues.
David MenningerAnalyst, ISG's Ventana Research
"Databricks is one of the few data platform vendors that has ventured into creating their own LLMs," Menninger said. "This may give them the opportunity to own more of the AI stack than other data platform providers. They have also done a very good job developing an ecosystem around their platform that provides fertile ground … to expand product capabilities and revenue."
Thrive Capital led Databricks' Series J funding round with co-leadership from Andreessen Horowitz, DST Global, GIC, Insight Partners and WCM Investment Management. Before this latest round, Databricks had raised $4 billion in total funding.
Spending the money
With $8.6 billion already secured and another $1.4 billion expected to close out its Series J funding round, Databricks plans to make additional investments in AI, finance more acquisitions and expand go-to-market efforts, according to a press release. In addition, the vendor said part of the funding will be used to provide liquidity -- make shares available for purchase and sale -- for current and former employees.
Each are logical ways to use the cash, according to Doug Henschen, an analyst at Constellation Research.
Given its previous funding, Databricks already had money to spend, he noted. But having a bigger bank account from which to draw is only beneficial against competition that includes close rival Snowflake; tech giants including AWS, Google Cloud and Microsoft; and now AI developers such as OpenAI and Anthropic.
"It's always good to have a cushion and a war chest," Henschen said. "Possibilities include more acquisitions, funding more internal organic product development and greasing the skids for market expansion."
Mike Leone, an analyst at Informa TechTarget's Enterprise Strategy Group, likewise said that having an extra $10 billion provides Databricks myriad opportunities to grow.
The funding comes on the heels of 60% year-over-year revenue growth during the fiscal quarter ended Oct. 31, according to Databricks. Included in that are more than 500 customers spending at least $1 million annually with the vendor.
In addition, Databricks' revenue run rate is expected to top $3 billion and the vendor anticipates being free cash flow positive during the fiscal quarter ended Jan. 31, 2025, it said.
The new funding has the potential to further that momentum, according to Leone.
"The AI opportunity for Databricks continues to be huge," he said. "They've made several acquisitions over the last couple years to expand their AI chops within their Databricks Data Intelligence Platform. I would expect that to continue throughout 2025. At the same time, they need to continue to invest in themselves to build out existing AI capabilities within their platform."
Global expansion represents another opportunity for Databricks, Leone continued. Each region has its own regulations. Funding could be used to help Databricks prepare its platform for use across regions. Meanwhile, providing liquidity could enable Databricks to improve the quality of its staff while retaining its most valuable employees.
"This is a big deal for Databricks so they can continue to attract top talent, while reducing turnover," Leone said.
While acquisitions and expansion are likely, Menninger suggested that Databricks focus at least some of the funding on better enabling existing customers to develop AI applications that meet their goals. Many AI Projects fail, often due to lack of proper data and AI governance. More governance capabilities, therefore, could be beneficial to retaining customers and attracting new ones.
"Enterprises still face issues getting AI investments into production," Menninger said. "Our research shows the top lesson enterprises have taken away from their investments to date is that they need better governance. Continued investments in AI and data governance would be welcomed by customers and prospects alike."
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
