Databricks just made one of the loudest moves in private tech this year.
The enterprise data and AI company has raised $4 billion at a $134 billion valuation, cementing its place among the most valuable private technology firms in the world. The round was led by Insight Partners, Fidelity Management & Research, and JP Morgan Asset Management, with backing from Andreessen Horowitz, BlackRock, and Blackstone.
For Databricks, this isn’t just about capital. It’s about time—and control.
A private giant growing fast
The funding comes only months after Databricks raised $1 billion at a $100 billion valuation, underscoring how quickly investor appetite has intensified around the company.
Databricks now sits in rare territory: a private firm competing directly with public cloud and data giants like Oracle and Snowflake, without the pressure of quarterly earnings or market volatility.
The company says its revenue run rate has climbed to $4.8 billion, representing roughly 55% year-over-year growth, a pace that few enterprise software companies can match at this scale.
Building the infrastructure behind AI
Founded in 2013 by a team of researchers led by CEO Ali Ghodsi, Databricks has never chased consumer attention.
Instead, it focuses on the less visible—but more durable—layer of technology: helping enterprises store, process, and activate massive volumes of data as they deploy AI-driven systems.
That position has become increasingly valuable as companies race to integrate AI into products, operations, and autonomous workflows. Databricks doesn’t sell a single tool. It embeds itself deep into how businesses run.
And once it’s there, switching becomes hard.
Research over short-term optics
A significant portion of the new funding will go toward expanding Databricks’ AI research efforts, including hiring thousands of new employees over time. Ghodsi has repeatedly argued that long-term research depth—not just product velocity—will define the next phase of enterprise AI.
Another portion of the capital will support secondary share sales, giving employees liquidity without forcing the company into an IPO.
That choice matters.
Why Databricks isn’t rushing to go public
As companies like OpenAI, Stripe, and SpaceX continue to grow at massive private valuations, Databricks reflects a broader shift across tech: going public is no longer the default milestone.
Deep private markets now offer something founders once needed public markets for—scale, patience, and optionality.
For Databricks, staying private means it can invest heavily in research, talent, and infrastructure without optimizing for short-term market sentiment.
Conclusion
Databricks isn’t trying to win the AI spotlight.
It’s building the backbone that makes enterprise AI work—and with $4 billion in fresh capital, it’s betting that quiet infrastructure, not flashy apps, will define the next decade of tech.
If that bet pays off, the most important AI company in the room may continue to be the one most users never see.