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Databricks Raises $5 Billion at $190 Billion Valuation

Databricks closes a $5 billion round at a $190 billion valuation, topping a $7 billion run rate as enterprise AI agent demand fuels 80% growth.

Stefan Trbojevic

Stefan Trbojevic

13 August 20262 min read
LinkedIn
Databricks editorial illustration with red branding

The takeaway

Enterprise AI value is accruing to the data and governance layer between models and production agents, not just to frontier labs.

Why it matters for builders

The durable value in enterprise AI sits in the infrastructure layer between raw models and production agents. Governance, data warehousing, and agent orchestration are becoming the categories enterprises actually pay for.

Databricks Raises $5 Billion at $190 Billion Valuation

Databricks closed a $5 billion funding round at a $190 billion valuation on Thursday, solidifying its place among the most valuable private companies in the data and AI industry. The round was led by Coatue, Blackstone, MGX, T. Rowe Price, and Sixth Street Growth, and arrives just six months after a prior round that valued the company at $134 billion.

What happened

The data and AI platform also disclosed it has crossed a $7 billion revenue run rate, growing more than 80% year-over-year in its second quarter. CEO Ali Ghodsi told CNBC that “demand is crazy,” adding that “everybody’s using these agents, AI agents, and the whole world is laser focused on agents, AI.”

Databricks said it will direct the capital toward enterprise AI capabilities, with emphasis on its Unity AI Gateway governance tool and the Genie agentic coworker. Its Lakebase database launch, which positions the company against Oracle and SAP, has already passed a $100 million revenue run rate, while the Lakehouse data warehousing tool has surpassed $1.5 billion.

Why it matters

The round confirms that enterprise AI infrastructure remains one of the market’s hottest corners even as public tech stocks wobble. Databricks has now eclipsed public-market rival Snowflake in value, and it joins a growing group of companies opting to sit out the IPO market in favor of private capital.

The trajectory also reflects a broader shift in enterprise AI spending: value is accruing to the data platforms and governance tooling that make agentic AI usable inside large organizations, not just to frontier model labs.

What it means for builders

For AI builders and automation engineers, the signal is clear. The durable value sits in the infrastructure layer between raw models and production agents. Governance (Unity AI Gateway), data warehousing (Lakehouse), and agent orchestration (Genie) are becoming the categories enterprises will actually pay for. The era of just picking a model and calling an API is giving way to managed platforms that handle data, cost, and control.

Enterprise AI infrastructure: data platforms connecting models, governance, and agents

The bigger picture

The raise lands as frontier labs Anthropic and OpenAI have both confidentially filed to go public, setting up a potentially transformative stretch for AI capital markets. Databricks’ decision to stay private shows that the strongest AI-infrastructure players can still access deep private funding on their own terms.

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Editorial notes

Reported by

Stefan Trbojevic

Edited by

n8n Lab Editorial

Published

13 August 2026

Updated

13 August 2026

AI disclosure: AI assisted with research and drafting. Factual claims are reviewed by an editor.

n8n Lab is an independent service provider. We are not affiliated with, endorsed by, or sponsored by n8n GmbH. “n8n” is a trademark of n8n GmbH and is used here only to describe the platform-specific implementation and automation services we provide.