As IPO markets begin to reopen cautiously, Databricks is sending a clear signal that public listings are no longer the only—or even preferred—route to scale. The data intelligence company has raised more than $4 billion in a Series L funding round, valuing it at $134 billion, a sharp increase from its $100 billion valuation just three months ago. The raise underscores deep confidence from private market investors at a time when many late-stage technology companies are reassessing the timing and relevance of going public.
This latest round marks Databricks’ third significant venture raise in less than a year and highlights its ambition to position itself as foundational infrastructure for the AI-driven enterprise. Rather than chasing short-term liquidity, the company is using private capital to accelerate long-term product bets across data, AI, and application development. The funding round was led by Insight Partners, Fidelity Investments, and J.P. Morgan Asset Management, reinforcing Databricks’ standing as one of the most strategically important players in enterprise AI.
A major focus of investment is product expansion. Databricks is building out Lakebase, a Postgres-based database designed for AI agents, following its $1 billion acquisition of Neon. Alongside this, the company is advancing its Agent Bricks platform and a growing suite of enterprise AI applications aimed at helping organizations operationalize AI on their proprietary data. Strategic partnerships also play a key role in this vision, with Databricks integrating leading foundation models through large-scale collaborations with Anthropic and OpenAI.
“The parallel rise of vibe coding and generative AI is accelerating the development of data intelligent applications in the enterprise,” Databricks said in a statement, adding that the new capital will support AI apps and agent development on proprietary data. Co-founder and CEO Ali Ghodsi echoed this sentiment, noting that “enterprises are rapidly reimagining how they build intelligent applications,” as the latest funding round underscores investor conviction in Databricks’ central role within the enterprise AI stack.
At a broader level, Databricks’ rapid valuation growth reflects a shift in market dynamics. With private capital still abundant for category-defining companies, staying private offers flexibility, speed, and insulation from public market volatility. For Databricks, the strategy appears clear: deepen its technological moat, entrench itself at the core of enterprise AI workflows, and define the next generation of data intelligence—on its own timeline.
