Databricks in talks to raise $5B at a $134B valuation as AI demand surges, reports

Databricks is back in the spotlight with a funding target that signals just how far the AI boom has carried the data infrastructure market. The company is in talks to raise $5 billion at a valuation of $134 billion, according to The Information, which reviewed investor documents and spoke with a person familiar with the discussions.

The figure puts Databricks at roughly 32 times its expected 2024 revenue of about $4.1 billion — a multiple that reflects both investor confidence and the intense competition shaping enterprise AI. “Databricks boosts sales forecast, driving valuation to $134 billion,” The Information reported.

This development follows an earlier report from The Wall Street Journal, which said Databricks was preparing to raise more than $1 billion at a valuation of $100 billion. Since then, the company has updated its sales projections twice. In September, it raised its target from $3.8 billion to $4 billion, and later raised it slightly further. That pace puts the company on track for 55% revenue growth this year, a rate that stands out in a market where many public software companies have slowed.

The Information added that Databricks’ gross margin is slipping faster than expected, falling to 74% from an earlier plan of 77%. Higher usage of its AI products is contributing to the drop. It’s a tradeoff more software companies are learning to manage: AI usage spikes drive revenue but come with heavier compute costs.

Founded in 2013 by Ali Ghodsi and UC Berkeley researchers, Databricks built its reputation by helping companies ingest, unify, and analyze massive datasets. Its platform now supports thousands of businesses, including Block, Shell, and Rivian. With over 20,000 customers and 8,000 employees, Databricks has grown into one of the most closely watched startups in enterprise software. That attention only intensified as investors began treating it as a likely candidate for one of the biggest tech IPOs of this cycle.

The numbers show why. Back in June, executives told investors the company was pacing $3.7 billion in annualized revenue with growth above 50%. That puts Databricks just behind Snowflake, which expects $4.5 billion this fiscal year but is growing at roughly half the speed. Snowflake’s current $65 billion market cap shows the gap between public-market pricing and the private premium Databricks now commands. Investors are placing bigger bets on companies positioned to define the next stage of AI infrastructure.

Part of that confidence stems from Databricks’ next project. Internally called “Lakebase,” the new effort is described as an AI-native database built for the latest wave of applications and autonomous agents. It’s an attempt to challenge longtime incumbents like Oracle and Microsoft by reshaping how enterprises organize data for AI workloads. The idea is simple: if every company is building around artificial intelligence, the database itself needs to evolve with it.

Profitability gives Databricks room to control its own timeline. There’s no pressure to rush toward an IPO, but the company is clearly preparing for a market where AI infrastructure players will define the next decade of software. Its backers — including Andreessen Horowitz, Thrive, Insight, and WCM Investment Management — have been waiting for this moment, and private markets appear willing to place large bets ahead of a public debut.

As public investors continue to react to swings in companies like Figma after their listings, private capital is flowing into startups that show both rapid scale and a clear AI-focused roadmap. Databricks fits that profile better than almost anyone in enterprise tech right now. Whether the latest round accelerates talk of an eventual IPO is still an open question. But one thing is clear: Databricks has positioned itself as one of the strongest contenders to lead the AI-heavy future of data systems — and investors are pricing that future far ahead of schedule.