Databricks has announced one of the largest private funding rounds in the technology sector to date, revealing it is raising more than $4 billion in a Series L investment that values the company at $134 billion. The announcement underscores Databricks’ rapid ascent as enterprises increasingly prioritize data-driven artificial intelligence, and it positions the company among the most highly valued private software firms globally.
Alongside the funding news, Databricks disclosed that it surpassed a $4.8 billion annualized revenue run rate during its third quarter, growing more than 55 percent year over year while maintaining positive free cash flow over the past 12 months.
The company’s financial performance highlights the breadth of its platform expansion. Databricks reported that both its Data Warehousing and AI product lines have each exceeded $1 billion in annualized revenue run rate, a milestone that signals strong enterprise adoption beyond its origins in data analytics. More than 700 customers are now consuming services at an annual run rate exceeding $1 million, while net revenue retention has remained above 140 percent, reflecting sustained expansion within existing accounts.
The Series L round was led by Insight Partners, Fidelity Management & Research Company, and J.P. Morgan Asset Management, with participation from a wide range of global institutional investors including Andreessen Horowitz, BlackRock, Blackstone, Coatue, GIC, MGX, NEA, Ontario Teachers’ Pension Plan, Robinhood Ventures, T. Rowe Price, Temasek, Thrive Capital, and Winslow Capital. The scale and composition of the investor group point to broad confidence in Databricks’ long-term role as a foundational platform for enterprise AI.
Databricks plans to deploy the new capital primarily to accelerate customer adoption of what it calls Data Intelligent Applications, a category emerging at the intersection of generative AI, data engineering, and application development. As enterprises explore new coding paradigms and experiment with AI agents, Databricks aims to provide an integrated stack that allows organizations to build intelligent applications directly on their proprietary data. Central to this approach is Lakebase, a serverless Postgres database designed to serve as a system of record for AI-driven workloads, combined with Databricks Apps as the user experience layer and Agent Bricks to support multi-agent systems.
Liquidity for Employees
Lakebase has already attracted thousands of customers within its first six months and is generating revenue at roughly twice the pace of Databricks’ Data Warehousing product at a comparable stage. The company views this momentum as evidence that enterprises are seeking unified platforms that bridge transactional data, analytics, and AI inference without sacrificing governance or performance. Databricks Apps is positioned to allow organizations to rapidly deploy secure, production-grade applications, while Agent Bricks is intended to simplify the development and scaling of AI agents that operate on enterprise data.
Beyond product development, Databricks indicated that a portion of the funding will be used to provide liquidity for employees, a common feature of late-stage private rounds at companies with extended timelines to public markets. The capital may also support targeted AI acquisitions and expanded research initiatives as competition intensifies among data and AI platform providers.
Chief executive and co-founder Ali Ghodsi framed the funding as a response to structural changes in how enterprises build software, emphasizing that generative AI is reshaping application architectures and data workflows. Investors echoed this view, pointing to Databricks’ ability to translate AI innovation into measurable enterprise outcomes while maintaining strong financial discipline.
As enterprises continue to operationalize AI at scale, Databricks’ latest funding round highlights the growing strategic importance of platforms that unify data management, analytics, and AI under a single architecture. With significant capital now in hand and revenue growth accelerating, the company appears positioned to play a central role in how organizations turn data into intelligent, production-ready applications.
Executive Insights FAQ
What does Databricks’ $134 billion valuation signal about the enterprise AI market?
It reflects strong investor confidence that enterprise AI platforms will become core infrastructure for global businesses.
How is Databricks generating revenue growth at this scale?
Growth is driven by expanding adoption across analytics, data warehousing, and AI products, with high retention among large enterprise customers.
What are Data Intelligent Applications?
They are applications that combine proprietary enterprise data with generative AI and intelligent agents to deliver dynamic, context-aware functionality.
Why is Lakebase strategically important?
Lakebase serves as a unified system of record, enabling transactional and AI workloads to run directly on trusted enterprise data.
How will this funding impact customers in the near term?
Customers can expect faster product innovation, deeper AI capabilities, and expanded tooling to build and deploy intelligent applications securely.
