--- title: Databricks Raised $7 Billion While SaaS Stocks Lost $285 Billion description: Databricks closed $11 billion in funding across two months at a flat $134 billion valuation while the SaaSpocalypse wiped $285 billion from enterprise software stocks. author: Darie Nani (Editor-in-Chief) date: 2026-02-15T15:18:33.000Z updated: 2026-02-26T17:55:08.041Z canonical: https://www.sovereignmagazine.com/article/databricks-raised-7-billion-while-saas-stocks-lost-285-billion image: https://cdn.nanimediahouse.com/databricks-san-francisco-ad.webp categories: Artificial Intelligence content_type: News region: Global publication: Sovereign Magazine about: - type: Organization name: Databricks --- [Databricks](https://www.databricks.com/company/newsroom/press-releases/databricks-grows-65-yoy-surpasses-5-4-billion-revenue-run-rate) closed a $7 billion round at a $134 billion valuation in February 2026, splitting $5 billion in equity from $2 billion in debt. The timing is hard to ignore. Over the same period, $285 billion was wiped from SaaS stocks in what analysts have called the SaaSpocalypse. Workday lost 40 per cent of its value and its CEO was forced out. [Salesforce](https://www.sovereignmagazine.com/article/the-ai-monetisation-reality-check-what-salesforce-s-revenue-miss) and ServiceNow each dropped roughly 7 per cent. Someone is losing money in enterprise software. It is not Databricks. ## Revenue hit $5.4 billion annualised, growing at 65 per cent Annualised revenue reached $5.4 billion based on the January quarter, up 65 per cent year over year. That number was supposed to be closer to 50 per cent. Growth accelerating at this revenue scale almost never happens. A quarter of that revenue ($1.4 billion annualised) comes from AI workloads, and the company turned free cash flow positive over the past 12 months. CEO Ali Ghodsi called the raise ‘discretionary rather than urgent’ and said there is no time pressure for an IPO. Goldman Sachs, Morgan Stanley, Glade Brook Capital, Neuberger Berman and the Qatar Investment Authority led the equity. JPMorgan led the debt. ## The $134 billion valuation only makes sense next to Snowflake A $134 billion valuation on $5.4 billion in revenue is 25x. The closest public comparison is Snowflake, which generates roughly $4.8 billion annualised and trades at $58 billion, or about 12x. Similar revenue, less than half the price. The gap comes down to growth rate and what investors think the future of enterprise data looks like. Databricks’ lakehouse architecture unifies warehousing, data lakes and AI workloads on one platform. Snowflake does warehousing well but does not cover the same surface area. Private market investors are betting that breadth wins. If they are wrong, early backers of this round face a painful markdown whenever Databricks eventually lists. ## $11 billion raised in two months, all at a flat valuation This is Databricks’ second raise in two months. It took $4 billion in December 2025 at the same $134 billion valuation. Flat pricing across $11 billion in capital is unusual. It reads like a company stockpiling cash for something specific rather than chasing a higher number for the sake of it. Ghodsi named one target: ‘We will double down on Lakebase so developers can create operational databases built for AI agents.’ Lakebase lets AI agents read and write enterprise data in real time, not just query historical datasets. If agents end up replacing the SaaS dashboards that humans currently use to interact with company data (which is exactly the thesis driving the SaaSpocalypse sell-off), the database layer underneath becomes the most valuable piece of the stack. Databricks now has $11 billion to make sure it owns that layer. ## Further Context **Q: Is Databricks more profitable than Snowflake?** Databricks turned free cash flow positive over the past 12 months on $5.4 billion in annualised revenue. Snowflake has been free cash flow positive for longer and carries higher gross margins (roughly 75 per cent product gross margin). However, Databricks is growing at 65 per cent year over year compared to Snowflake’s roughly 29 per cent. On a Rule of 40 basis (growth rate plus profit margin), Databricks scores higher. Profitability comparisons are complicated by the fact that Databricks is private and does not disclose full financial statements. **Q: What is data lakehouse architecture?** A data lakehouse combines the low-cost, flexible storage of a data lake with the structured query and governance features of a data warehouse. Traditional architectures required companies to maintain both systems separately, copying data between them. A lakehouse stores all data in one place (typically cloud object storage) and applies warehouse-style indexing and access controls on top. Databricks pioneered the term and built its platform around the concept. Competitors including Google BigQuery and Amazon Redshift have since adopted similar hybrid approaches. **Q: Who is bigger, Snowflake or Databricks?** Databricks has now passed Snowflake in annualised revenue ($5.4 billion versus roughly $4.8 billion), customer count at the $1 million-plus tier and private market valuation ($134 billion versus Snowflake’s $58 billion public market capitalisation). Snowflake remains more established in pure data warehousing and has a longer track record of profitability as a public company. Databricks has broader product surface area, covering warehousing, data engineering, machine learning and now operational databases for AI agents through Lakebase.