Databricks announced the launch of a new round of finance, with an updated estimate of $188.0 billion. The company indicated that the funds would be released later in the summer and that the exact size of the fund-raising was not disclosed. A number of external sources subsequently reported that the current round was about $3 billion in size, with Coatue as the lead recipient.

The company, which was founded in 2013, originally started with large data and cloud-based analysis software, has significantly accelerated the pace of financing for almost a year and a half, while shifting the focus of the market to enterprise level AI. The continued increase in valuations is also linked to the expansion of their product lines and changes in client demand.

The valuation has continued to rise for almost a year and a half.

  • December 2024, $10 billion in financing, valued $62 billion
  • September 2025, financing $1 billion, valuation $100 billion
  • In February 2026, $5 billion L rounds of financing were completed, valued at $134 billion

Only five months later, the company ' s valuation rose to $188.0 billion. TechCrunch refers to the investor ' s assertion that the demand for the current round of transactions is strong and that the company has therefore chosen to disclose new valuations in advance, even before the funds are available.

Enterprise AI becomes the new main line

The early core business of Databricks was to help enterprises store big data and carry out rapid analysis at the cloud end. Because of its own large business data landscape, companies move faster into more demanding enterprise-level applications for security, governance and deployment after generating AI has entered the business market.

In recent times, Databricks has continued to introduce AI-related products, including the AIAgent database Lakebase, the AI Gateway Unity, and several Agent-based tools. As these products land, the company ' s positioning in the outside world is further shifting from traditional SaaS manufacturers to AI infrastructure and application platform providers.

Open source model low deployment cost

Databricks was also mentioned as one of the representative companies in the trend for enterprises to adopt lower-cost open source models. In particular, the company appreciates the performance of the GLM 5.2 of the Chinese team Z.ai in the code-generated scene and sees it as an option to control AI costs.

In addition to the model itself, Databricks also emphasized that the Agent coding tool, which runs around the model, also significantly affects costs. Previous studies by the company have found that the open-source tool Pi has performed well in context management and has been able to reduce the cost of use without significantly sacrificing quality.

This judgement also reflects the changing focus of enterprises when they deploy AI. Markets are no longer looking only at a single model capacity, and the accompanying tools, governance capacity and overall cost structure are becoming an important basis for enterprise procurement and capital pricing.