The unified data and AI platform strengthens its position amid soaring enterprise demand for AI-native infrastructure

Databricks is reportedly in discussions to raise new capital at a valuation above $130 billion, marking a ~30% increase over its last financing round just two months ago. The potential raise underscores the company’s accelerating growth and its importance in the rapidly evolving AI economy.

Founded in 2013 and built on the research behind Apache Spark, Databricks has grown into one of the world’s most influential data and AI platforms. Its core mission—unifying data engineering, analytics, governance, and AI model development—has become foundational as enterprises race to adopt AI-driven workflows.

Enterprise AI demand pushes Databricks to new highs

The company has been aggressively expanding its AI offerings, including:

• Databricks AI/BI, enabling natural language querying of enterprise data
• DBRX, its open-source LLM designed for enterprise workloads
• AI agents and tools that automate knowledge work and white-collar tasks

These innovations have helped Databricks surpass $4 billion in annualized revenue, growing 50% year over year, while becoming free-cash-flow positive—a rare milestone for a private company of its scale.

Its AI-specific revenue alone has exceeded $1 billion annualized, reflecting Databricks’ unique position at the intersection of data infrastructure and model development.

Competition with Snowflake intensifies

The ongoing rivalry between Databricks and Snowflake continues to shape the enterprise data landscape. Both companies now generate similar levels of revenue, but with key distinctions:

• Databricks leads on AI-native workloads, unifying data + model training within one platform
• Snowflake leads on cash flow generation and focuses heavily on cloud data warehousing
• Both companies compete for the same CIO budgets as enterprises increasingly standardize on a single platform for data + AI

Snowflake’s leadership has recently downplayed valuation comparisons, but the acceleration of Databricks’ AI initiatives suggests the competitive gap may evolve quickly.

Fuel for acquisitions, research, and expansion

If completed, the prospective capital raise would give Databricks additional flexibility to:

• Acquire AI-native startups and IP
• Hire top ML researchers and infrastructure engineers
• Expand its open-source ecosystem
• Deepen its investment into agents, retrieval, and real-time inference

The company has already completed several acquisitions over the past few years—including MosaicML, Okera, and Rubicon—to strengthen its AI stack.

Databricks now approaches 10,000 employees globally and remains one of the most anticipated private companies on the path to an eventual IPO. CEO Ali Ghodsi has repeatedly said he enjoys operating as a private company, though Databricks continues to run structured liquidity programs for employees and early investors.

A defining infrastructure player in the AI era

As AI adoption accelerates across every sector, Databricks’ unified approach to data, governance, and model development positions it as a critical pillar in enterprise transformation. Its trajectory—both in revenue and valuation—reflects a broader shift: organizations increasingly want a single, scalable platform to manage everything from raw data to production-grade AI agents.

In a market where the winners will likely define the next decade of enterprise software, Databricks remains one of the most strategically significant companies shaping how businesses build, deploy, and operationalize AI at scale.