Databricks Reaches $188B Valuation in New Funding Round

Databricks has strengthened its position as one of the biggest winners of the AI boom after announcing a new funding round that values the company at $188 billion. The investment was led by Coatue, continuing the company’s remarkable fundraising momentum over the past year and a half.

While Databricks confirmed the new financing, it did not reveal the exact amount being raised. The company noted that the transaction has not officially closed and that the funds are expected to be received later this summer. However, several media reports have estimated the funding round at approximately $3 billion.

Although companies typically announce funding after a deal closes, one venture capitalist told TechCrunch that investor demand for the round was so strong that Databricks had little reason to keep its latest valuation private.

The announcement marks another milestone in Databricks’ rapid transformation from a cloud data analytics company into one of the leading enterprise AI providers.

Its fundraising streak has been particularly impressive. Just five months ago, in February, Databricks completed a $5 billion Series L financing at a $134 billion valuation. Before that, the company secured $1 billion in September 2025, valuing the business at $100 billion. Earlier still, in December 2024, Databricks raised a then-record $10 billion funding round at a $62 billion valuation.

The company’s repeated fundraising announcements have even sparked jokes online about exhausting the alphabet of funding rounds. One social media user joked, “Turning on alerts for when we get a Series AA.”

Founded in 2013, Databricks originally built its reputation during the era of big data by helping enterprises store massive amounts of information in the cloud while delivering fast analytics. That foundation ultimately became a major advantage as artificial intelligence adoption accelerated.

Because many businesses already relied on Databricks to manage critical enterprise data, the company was well positioned to offer AI products with the security, governance, and reliability expected by enterprise customers.

Over the past few years, Databricks has significantly expanded its AI portfolio. The company introduced Lakebase, a database designed specifically for AI agents, Unity, its AI gateway, and Omnigent, a “meta-harness” that manages multiple AI agents simultaneously.

Databricks has also become one of the most prominent enterprise supporters of affordable Chinese open-weight AI models, a growing trend throughout 2026 as companies look to reduce AI operating costs. Among those models, the company has been a strong advocate for Z.ai’s GLM 5.2, particularly for software development tasks.

Last week, CEO Ali Ghodsi shared results from internal testing conducted across the company’s 3,000 software engineers to better understand AI development costs. According to the company’s benchmark, open-source models—and GLM 5.2 in particular—were capable of handling even highly complex coding tasks while costing less overall than proprietary models from Anthropic and OpenAI.

The study also revealed that selecting the right AI coding harness can influence costs just as much as choosing the underlying AI model. Databricks found that the open-source harness Pi performed particularly well by efficiently managing context around prompts, helping lower costs without reducing output quality.

The company emphasized that no single harness is universally the cheapest option. Instead, it concluded that overall AI efficiency depends on a combination of both model selection and the software layer that manages interactions with those models.

Databricks’ steady expansion into enterprise AI has reshaped how investors view the company. Although it was not originally founded as an AI startup, its successful pivot has earned it the market’s AI premium, fueling higher valuations with each successive funding round.

As TechCrunch previously noted, enthusiasm around artificial intelligence has become so widespread that even sandwich chain Jersey Mike’s referenced AI 22 times in its S-1 filing, highlighting just how influential the technology has become across industries.

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