“AI Bubble” maybe a thing in the public markets, but it certainly doesn’t seem to be applying to private markets, and Databricks has just proven that. The cloud-first data intelligence platform has raised one of the largest private funding rounds in enterprise software, securing over $4 billion and reaching a massive $134 billion valuation.
The funding was led by heavyweights such ans Insight Partners, Fidelity, and J.P. Morgan, with participation from Andreessen Horowitz, BlackRock, and Blackstone, signaling broad confidence in Databricks’ growth trajectory. The raise comes amid a $4.8 billion revenue run rate and more than 55% year-over-year growth, driven by adoption of both its data warehousing tools and AI products, each now surpassing the $1 billion run rate mark.
The capital injection will fuel multiple strategic priorities for Databricks. The SF based data and AI powerhouse plans to accelerate development of AI-driven products, expand its platform capabilities, and invest in global growth. CEO Ali Ghodsi has highlighted plans to hire thousands of engineers, AI researchers, and technical staff across multiple geographies. The funding will also allow for acquisitions and strategic partnerships. Meanwhile, secondary share sales are expected to provide liquidity for employees and early investors, a common feature in large private rounds.
Founded in 2013, Databricks has become a leading player in the intersection of data engineering, analytics, and AI. Its Data Intelligence Platform allows enterprises to store, process, govern, and activate large-scale datasets, enabling organizations to build production-grade AI models efficiently. The platform’s flexibility has attracted tens of thousands of customers globally, including many Fortune 500 companies.
While the company has also discussed going public in the past, Databricks has not announced a timeline for an IPO. And now, the latest capital round provides the company with the flexibility to continue scaling and innovating without immediate pressure from public markets. The development comes at a time when generative AI and advanced machine learning are gaining attention, but the real driver of successful AI in enterprises is the underlying infrastructure.
But Databricks’ growth has not been without bumps, as the company has faced significant technical setbacks, legal disputes, and customer-facing issues in recent times. For example, in May 2025, users reported a significant service disruption affecting Azure Databricks in the UK South and West regions, where overheating storage nodes caused outages and performance degradation for several hours. Meanwhile, on the legal front, Databricks and its subsidiary MosaicML have been named in multiple class-action copyright infringement lawsuits in 2024 and 2025, alleging that copyrighted books were used without permission to train large language models.
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