- Databricks has signed a term sheet for a new strategic round at a $188 billion valuation, led by Coatue Management, with the deal expected to close later this summer.
- The valuation marks a 40% jump in five months, from $134 billion in February, and an 88% rise in under a year, as investors price the enterprise AI governance layer at a premium over the model builders beneath it.
- New capital will go into Unity AI Gateway, Genie, and Lakebase: three products built on the premise that controlling AI costs and access is worth more in the long term than building AI itself.
Seven academics from UC Berkeley founded Databricks in 2013 to commercialise Apache Spark, a data processing engine they had built in a university lab. Twelve years later, their company is signing term sheets at a $188 billion valuation — higher than Goldman Sachs, higher than IBM, and closing in on Salesforce — without ever having gone public.
Databricks has signed a term sheet for a new strategic funding round at a $188 billion valuation, led by existing investor Coatue Management, with participation from new and returning investors. The round is expected to close later this summer and is the company’s second major financing event of the year, arriving five months after a $7 billion raise at $134 billion in February 2026.
What Databricks does
Databricks runs a cloud platform — its “data lakehouse” — that gives enterprises a single place to store, process, govern, and act on their data.
The problem it is solving is one most large organisations know intimately: data is scattered across dozens of disconnected systems, AI models sit on top of that mess, and nobody has clear control over what the AI is doing, what it costs, or whether it can be trusted.
Databricks unifies those layers. Its Unity AI Gateway manages which models employees can access, and tracks spend across them. Its Genie product turns that governed data into answers and actions without requiring a data engineer in the loop. Its newest product, Lakebase, is a serverless Postgres database built specifically for AI agents, meaning it can serve live, structured data to autonomous AI workflows without human intervention.
More than 20,000 organisations use the platform, including adidas, AT&T, Mastercard, and 70% of the Fortune 500. The company reported a $5.4 billion annualised revenue run rate in February 2026, up 65% year-on-year, with AI products alone generating $1.4 billion in annualised revenue.
The founders and the team
Databricks was co-founded by chief executive Ali Ghodsi, chief technology officer Matei Zaharia, executive chair Ion Stoica, Patrick Wendell, Reynold Xin, Andy Konwinski, and Arsalan Tavakoli-Shiraji — all former members of UC Berkeley’s AMPLab research group.
The company is headquartered in San Francisco and employs approximately 9,000 people globally.
The round and the investor
The new round has not yet disclosed its total size, investor list beyond Coatue, or a per-share price. Coatue, the New York-based crossover fund founded in 1999, has backed Databricks since its Series E in 2019. The firm has 178 unicorns in its portfolio, including OpenAI, Anthropic, Snowflake, and Instacart. It co-led Anthropic’s $65 billion Series H in May 2026 and has backed OpenAI across multiple rounds, making it one of the few investors with sizeable positions across all three of the industry’s most contested private valuations simultaneously.
“Enterprises are moving from tokenmaxxing to valuemaxxing. They don’t want to burn expensive tokens on the smartest model for every task — they want the best outcome per dollar. That means having the freedom to choose the right AI for the job. This new capital lets us keep pushing our multi-AI strategy forward to meet massive customer demand,” said Ghodsi.
Databricks has raised approximately $20.2 billion to date, most recently across its Series L round and this new strategic round. Other major investors across its cap table include Andreessen Horowitz, Insight Partners, Goldman Sachs, JPMorgan Chase, Morgan Stanley, Thrive Capital, the Qatar Investment Authority, and Blackstone.
The competitive picture
Databricks is not the only company chasing the enterprise AI governance layer. Snowflake, trading at a market cap of roughly $90 billion, is building a similar position with its Cortex AI platform, offering model routing and data governance bundled into its existing data warehouse. Microsoft is embedding Copilot and Azure AI Foundry directly into enterprise software contracts, making it a default rather than a choice. Google’s Vertex AI platform and AWS SageMaker give hyperscaler customers managed model hosting without switching costs.
What separates Databricks is its independence: it is not trying to sell cloud compute or an adjacent product, and its governance tools are designed to work across models from multiple providers simultaneously, not just its own stack.
What comes next
The global enterprise AI market was valued at $30.2 billion in 2025 and is projected to reach $155.2 billion by 2030, growing at a CAGR of 37.6%, according to Grand View Research.
Databricks sits at the intersection of that market and the broader data platform layer beneath it, a position it has spent twelve years building and that competitors would take years to replicate from scratch. Databricks was reportedly in talks at up to $175 billion as recently as June, so this term sheet lands well above even that chatter.
Ghodsi has told investors Databricks is IPO-bound, potentially as early as 2027, while calling 2026 the “worst year” to go public given the volume of high-profile listings already scheduled. At $188 billion on a term sheet, the more interesting question is whether the governance layer of enterprise AI is structurally defensible once the hyperscalers decide to give it away for free inside existing cloud contracts.
