Databricks completed a $10 billion Series J funding round that values the company at $62 billion. Thrive Capital leads this investment, which also includes participation from Andreessen Horowitz, DST Global, GIC, Insight Partners, and WCM Investment Management. The round includes new investors such as ICONIQ Growth, MGX, Sands Capital, and Wellington Management. The company reported an annualized revenue run-rate of $7 billion in August 2026, which reflects year-over-year growth of over 60%. The company expects to achieve positive free cash flow in the fourth quarter ending January 31, 2025. This expansion follows a period of strong momentum. The data warehousing product reached a revenue run-rate of more than $1 billion in less than four years from general availability. The company maintains more than 700 customers consuming at an annual revenue run-rate of more than $1 million. Its net retention rate remains above 140%. The company’s intelligent data warehousing product achieved a $600 million revenue run-rate, growing more than 150% year-over-year. A September 2026 PitchBook initiation report estimated an operating value near $69 billion, a figure that sits materially below the $190 billion primary mark and offers limited downside protection.
The company uses this capital to expand AI products like Lakebase and Agent Bricks. Lakebase, a serverless PostgreSQL database, grows at twice the pace of the data warehousing product and attracts thousands of customers within its first six months of availability. Agent Bricks provides an engine for multi-agent workflows. Databricks Apps acts as the user-facing experience layer. These tools help customers develop AI applications and agent-based tools using proprietary data. This approach follows the parallel rise of "vibe coding" and generative AI. Lakebase serves as the system of record for AI-era workloads. Databricks Apps enables organizations to build and deploy data and AI applications quickly and securely. Agent Bricks simplifies the creation and scaling of high-quality agents using an organization’s own data. The company continues to invest in hiring AI researchers to support these workloads. The company also plans to add thousands of employees in Asia, Europe, and Latin America. Naveen Rao, the former AI chief, stepped down in September 2025 to launch Unconventional, Inc. You should watch if the loss of such specialized leadership affects product velocity. Does the departure of a co-founder impact long-term stability?
Snowflake Cortex AI provides chat experiences and no-code interfaces to compete for enterprise workloads. Snowflake Cortex Analyst and Snowflake Cortex Search entered public preview recently. Databricks uses Lakebase to merge OLTP and OLAP workloads without an ETL bridge. This integration helps users build AI-powered internal apps that require low-latency reads on operational and historical context without sync jobs. Snowflake provides Document AI to extract content and Snowflake Copilot for text-to-SQL assistance. The Snowflake Model Registry and Snowflake Feature Store allow teams to manage models across the machine learning lifecycle. Snowflake also provides the Snowflake Arctic open-source large language model and the ability to customize models through serverless fine-tuning. To avoid data duplication, Databricks provides Delta Direct and UniForm, which allow Snowflake to query Delta tables. The industry experiences a massive governance gap. While 97% of companies deployed AI agents in the past year, only 38% of knowledge workers use them for real work according to McKinsey data from 2025. A Retool 2026 survey of 307 CTOs, CIOs, and CISOs found that only 8% describe their internal-tool governance as strong. Twenty-two percent of those leaders reported at least one production incident from an AI-generated tool in the past 12 months. Training and inference costs for enterprise-grade workloads increased approximately 3.2 times between 2024 and 2026. Most large programs still require a Databricks consulting partner to sequence these integrations safely.
