Databricks, a leading provider of data analytics and AI infrastructure, has secured $15.3 billion in new financing, significantly bolstering its position in the rapidly evolving AI market.
The funding package consists of $10 billion in Series J equity financing and a $5.25 billion credit facility arranged by JPMorgan Chase alongside other major financial institutions including Barclays, Citi, Goldman Sachs, and Morgan Stanley. This investment values the San Francisco-based company at $62 billion and brings its total funding to approximately $19 billion since its founding in 2013.
Meta's participation as a strategic investor is particularly significant, deepening an already productive technical relationship. "Thousands of customers are using Llama on Databricks and we have been working closely with Meta on how to best serve those enterprise customers with Llama," explained Databricks co-founder and CEO Ali Ghodsi. "It naturally made sense for both parties to deepen that partnership through this investment."
The collaboration between Databricks and Meta extends beyond financial investment. Databricks recently recognized Meta as its "AI Partner of the Year" for empowering customers to build and deploy AI agent systems using Llama models. Meta's leadership in open-source models has been foundational to Databricks' Mosaic AI capabilities, with their joint engineering efforts helping enterprise customers accelerate adoption of generative AI technologies.
Databricks plans to invest the new capital in developing AI products, funding acquisitions, and expanding its international operations. The company has experienced accelerated growth—exceeding 60% year-over-year in recent quarters—largely driven by unprecedented interest in artificial intelligence. With more than 10,000 organizations including Comcast, Block, Rivian, and Shell relying on its Data Intelligence Platform, Databricks is positioned to capitalize on the growing enterprise demand for AI-ready data infrastructure.
As enterprises increasingly recognize the potential of generative AI, Databricks' unified platform approach addresses a critical market need. According to recent research from Economist Impact, only 22% of organizations believe their current architecture can support AI workloads without modifications, highlighting the significant opportunity for Databricks' integrated data and AI solutions.