Databricks Reaches a US$134 Billion Valuation

Databricks announced it is raising a Series L investment exceeding US$4 billion, valuing the company at US$134 billion. Concurrently, the company crossed a US$4.8 billion revenue run-rate during its 3Q25, reporting over 55% year-over-year growth. This financial injection capitalizes on the expansion of products focused on data intelligent applications, including Lakebase, Agent Bricks, and Databricks Apps.

"The convergence of Generative AI with new coding paradigms is opening the door to entirely new workloads. With this investment, we are deepening our commitment to help every organization innovate with AI on its own data," says Ali Ghodsi, Co-Founder and CEO, Databricks. 

The decision by Databricks to pursue a Series L funding round, which is an uncommon stage in the startup life cycle, reflects private market confidence in the data platform and AI sector. This move occurs when the window for Initial Public Offerings (IPOs) is uncertain, prioritizing the securing of significant capital without subjecting the company to public scrutiny, which allows for greater strategic agility for investment.

The relevance of this capital injection resides in the organizational need to integrate data intelligence solutions that allow for the development and deployment of AI agents on proprietary data. The market is undergoing a structural shift toward Data Intelligent Applications, where the capability to process, govern, and apply AI models to large volumes of transactional data is a crucial competitive differentiator. 

Financial Performance and Capital Allocation

The announcement of the Series L funding, exceeding US$4 billion, is based on solid operational and financial results. Databricks reported surpassing a US$4.8 billion revenue run-rate during 3Q25, an increase exceeding 55% year over year. Within this total, the company highlighted two key milestones:

• A revenue run-rate exceeding US$1 billion generated by its AI products.

• A revenue run-rate also exceeding US$1 billion originating from its Data Warehousing business, a milestone reached in fewer than four years from general availability.

Additionally, Databricks has maintained positive free cash flow over the last 12 months and a net retention rate sustaining over 140%. More than seven hundred customers consume services with an annual revenue run-rate exceeding US$1 million. 

The capital will be used to fund the development of strategic products, including Lakebase, Agent Bricks, and Databricks Apps. Specifically, the funds are expected to support the following:

• Accelerating AI Research and Development: Deepening research and development in AI, which could include future acquisitions of key technology or talent.

• Employee Liquidity: Providing liquidity for employees, a common practice for companies delaying an IPO.

• Expansion of Key Platforms: Boosting the growth of platforms dedicated to data intelligent applications.

Strategic Platform Advancements

The investment is directly linked to the advancement of the product offering designed for the Generative AI era. Databricks is focusing its development on Lakebase, Databricks Apps, and Agent Bricks.

This product strategy aims to address the corporate need to build a new generation of applications that integrate transactional data and Large Language Models (LLMs) efficiently. The company said in the Dec. 16, 2025, press release that the parallel rise of "vibe coding and generative AI is accelerating the development of data intelligent applications in the enterprise." The capital is intended to help customers build AI applications and agents on their proprietary data, leveraging Lakebase as the system of record, Databricks Apps as the user experience layer, and Agent Bricks to power multi-agent systems.

The strategic focus of Databricks on the capitalization and development of solutions for AI infrastructure underscores the market transition toward unified data platforms. This financing confirms the expectation of sustained growth and product innovation in the sector.