Databricks is moving into a new phase of scale as growth accelerates and investor confidence reaches rare heights. The data and AI company has reported year over year revenue growth above 55 percent while simultaneously closing one of the largest private funding rounds ever recorded in the software sector.
The company says it crossed an annualized revenue run rate of more than 4.8 billion US dollars during the third quarter. At the same time, Databricks secured over four billion US dollars in Series L financing, pushing its valuation to roughly 134 billion US dollars. Few private technology companies globally operate at this scale, let alone maintain growth at this pace.
The size of the financing round alone places Databricks in elite territory. The round was led by Insight Partners, Fidelity Management and Research Company, and J.P. Morgan Asset Management. They were joined by a deep roster of long-time and new backers, including Andreessen Horowitz, BlackRock, Blackstone, Coatue, GIC, NEA, Temasek, and Thrive Capital.
Investor participation at this level reflects a clear belief that Databricks sits at the center of a long-term shift in how enterprises manage data and deploy AI. This is not short-term momentum chasing. It is a bet on infrastructure that underpins modern analytics, machine learning, and generative AI workloads across industries.
From a European perspective, the numbers stand out sharply. Multibillion-dollar revenue, sustained growth above 50 percent, and a valuation well into twelve figures remain extremely rare for privately held software companies. Yet scale alone does not settle the question of profitability.
Databricks has reported positive free cash flow over the last twelve months. That milestone matters. Still, free cash flow does not automatically translate into durable operating profitability. Fast-growing infrastructure companies continue to reinvest aggressively in compute, platform expansion, global sales teams, and research. These costs can suppress margins for years.
The latest funding round therefore signals confidence in Databricks’ future position rather than confirmation that the company has reached financial maturity. Investors appear willing to trade near-term profit certainty for long-term platform dominance.
A major driver behind this confidence is the company’s expanding revenue mix. Databricks now generates more than one billion US dollars annually from its data warehousing products and its growing portfolio of AI offerings. This blend positions the company at the intersection of two markets that continue to converge.
Enterprise demand for data-driven systems has surged as generative AI moves from experimentation into production. Companies no longer want fragmented stacks. They want unified platforms that can ingest data, train models, deploy applications, and operate AI systems securely at scale.
Databricks has benefited directly from this shift. The company reports a net revenue retention rate above 140 percent, indicating that existing customers continue to expand their usage year after year. More than 700 customers now generate over one million US dollars in annual spend on the platform.
Its customer base spans more than 20,000 organizations worldwide. That group includes global brands such as adidas, Bayer, and Mastercard, along with over 60 percent of Fortune 500 companies. Adoption at that level reinforces Databricks’ position as core infrastructure rather than optional tooling.
The new capital will be deployed across several strategic product initiatives that signal where Databricks believes the next phase of growth will come from. One major focus is Lakebase, a serverless Postgres database designed specifically for AI-native applications.
According to the company, Lakebase has attracted thousands of customers within months of launch and is growing faster than its original data warehousing business. That early traction suggests strong demand for databases that integrate seamlessly with AI workflows rather than sitting alongside them.
Databricks is also expanding Databricks Apps, a development and deployment environment that allows teams to build data-centric and AI-powered applications directly on the platform. This moves the company further up the stack, from infrastructure provider toward full application enablement.
Another priority area is Agent Bricks, a product aimed at helping enterprises design, deploy, and operate complex AI agents using their own proprietary data. As businesses explore agent-based systems for automation and decision support, Databricks is positioning itself as the operational backbone for those systems.
Together, these initiatives reflect a broader ambition. Databricks wants to become the default platform for what it describes as data-intelligent applications. That means handling everything from storage and analytics to model execution, orchestration, and governance within one environment.
Not all of the new funding is earmarked for product expansion. Databricks plans to allocate a portion of the capital toward employee liquidity, providing long-time staff with an opportunity to realize value after years of growth.
The company is also expected to pursue strategic acquisitions in AI and data infrastructure, as well as expand its internal research efforts. These moves suggest Databricks intends to deepen its technical moat rather than slow down after reaching scale.
The Series L round reinforces Databricks’ ambition to shape the global market for data and AI platforms. Few private companies have the balance sheet, customer reach, and investor backing to attempt this at such scale.
Still, one question remains open. Can Databricks convert its rapid growth into stable, long-term profitability without sacrificing momentum. The answer will define the next chapter of the company’s evolution as it moves closer to the public markets and deeper into enterprise operations worldwide.
For now, Databricks has secured the capital, confidence, and customer demand needed to keep pushing forward. The challenge ahead is execution at unprecedented scale.
