Databricks closed a $5 billion strategic funding round on August 13, 2026, at a $190 billion valuation. This amount is a 42 percent jump from the $134 billion valuation from February 2026. The company reports a $7 billion revenue run rate and 80 percent year-over-year growth. This growth rate is much higher than the 30 percent growth rate reported by Snowflake. I find this $190 billion price tag to be a massive bet on the company maintaining its momentum as it scales.
The funding history of a private giant
The company has completed 12 primary funding rounds since its inception. In the period between 2013 and 2016, Databricks raised approximately $47 million through Series A, B, and C rounds. The Series A round at a $48.68 million valuation occurred in 2013. The Series B round in 2014 raised $34 million at a $250 million valuation. The Series C round in 2016 raised $60.37 million at a $520 million valuation. In 2017, the Series D round raised $140 million at a $1 billion valuation.
The company accelerated its fundraising in 2019. The Series E round raised $250 million at a $2.81 billion valuation, while the Series F round raised $400 million at a $6.2 billion valuation. Both rounds included investors like Microsoft and Andreessen Horowitz. In 2021, the Series G round raised $1 billion at a $28 billion valuation. The Series H round followed in 2021, raising $1.63 billion at a $38 billion valuation.
The most recent years show much larger capital injections. In 2023, the Series I round raised $685 million at a $43 billion valuation. In December 2024, the Series J round raised $10 billion at a $62 billion valuation. The Series K round in September 2025 raised $1.13 billion at a $100 billion valuation. In February 2026, the Series L round raised $5 billion at a $134 billion valuation.
| Round | Date | Amount | Valuation |
|---|---|---|---|
| Series A-C | 2013-2016 | $47 million | $48.68 million |
| Series D | 2017 | $140 million | $1 billion |
| Series E | 2019 | $250 million | $2.81 billion |
| Series F | 2019 | $400 million | $6.2 billion |
| Series G | 2021 | $1 billion | $28 billion |
| Series H | 2021 | $1.63 billion | $38 billion |
| Series I | 2023 | $685 million | $43 billion |
| Series J | 2024 | $10 billion | $62 billion |
| Series K | 2025 | $1.13 billion | $100 billion |
| Series L | 2026 | $5 billion | $134 billion |
| Strategic | 2026 | $5 billion | $190 billion |
Comparing Databricks to Snowflake
Databricks is a private company, so its valuation is set by private investors. Snowflake is a public company that listed on the NYSE in September 2020. The two companies compete for the same enterprise data and AI workloads. Databricks focuses on an open lakehouse architecture that uses formats like Delta Lake and Parquet. Snowflake uses a managed, proprietary data cloud.
You should know that the market cap of Snowflake is set daily by public trading, whereas the Databricks valuation comes from private deals. In August 2026, Snowflake has a market cap of roughly $114 billion. This is much lower than the $190 billion valuation for Databricks. Databricks has a revenue run rate of $7 billion, while Snowflake has a product revenue of $4.47 billion for fiscal year 2026. The growth rate for Databricks is 80 percent, which is higher than the 30 percent growth rate for Snowflake.
| Metric | Databricks | Snowflake |
|---|---|---|
| Company status | Private | Public |
| Valuation / Market Cap | $190B | $114B |
| Revenue | $7B+ ARR | $4.47B |
| Growth Rate | 80% | 30% |
| Core architecture | Open lakehouse | Managed proprietary cloud |
| AI product | Mosaic AI / Genie | Cortex AI |
The expansion of AI products
Databricks uses its capital to grow its AI product suite. The company includes Unity AI Gateway, Genie, and Lakebase in its strategy. Unity AI Gateway helps enterprises manage and control the costs of multiple AI models. Genie is an AI coworker that converts business data into answers and actions. Lakebase is a serverless Postgres database designed for AI agents.
The company focuses on the AI layer by providing infrastructure for enterprise agents. These products address the gap between scattered data and AI tools. The Lakebase unit alone has a revenue run rate exceeding $100 million. The Lakehouse data warehousing tool has a run rate above $1.5 billion. The company also includes Mosaic AI to help enterprises build and deploy generative AI models.
The company continues to acquire businesses to support this growth. In 2023, it bought MosaicML to improve its generative AI capabilities. In 2024, it bought the data management company Tabular for $2 billion. In 2025, it acquired the serverless database company Neon for $1 billion. These moves help the company close the context gap for enterprises.
The exit of Naveen Rao
Leadership changes in the company add complexity to the IPO discussion. Naveen Rao left his role as the AI chief in September 2025. He left to start a new company called Unconventional, Inc., which focuses on AI hardware. Databricks is an early investor in his new venture. Rao joined Databricks after the company acquired MosaicML in 2023.
His departure follows a standard pattern for many technical leaders after an acquisition. Most founders in Silicon Valley receive retention packages that last 18 to 24 months. Since Rao led the AI division from mid-2023 until late 2025, his exit fits this two-year window. The company continues to push its AI goals despite his transition to an advisory role.
The loss of a high-profile leader can affect investor confidence. Some analysts question if leadership stability will remain high as the company approaches a public listing. Databricks has a large leadership team to manage these transitions. The company must prove it can maintain its AI momentum without Rao’s direct involvement.
Why the 2026 IPO is unlikely
The company is staying private for now. CEO Ali Ghodsi told Bloomberg that 2026 is a "terrible" year to list. He cited the presence of SpaceX, Anthropic, and OpenAI in the public market. These large offerings consume a lot of investor capital and attention. Databricks does not want to compete for attention during such a crowded period.
The company also has enough cash to avoid the public markets. It has raised billions in private rounds at rising valuations. The latest strategic round was led by Coatue and includes Blackstone and T. Rowe Price. These investors provide liquidity without a public offering. The company can grow without the quarterly pressure of public earnings.
A listing in 2027 or later seems more plausible. The company is IPO-ready and wants to wait for better market conditions. An IPO would allow employees to sell their shares, which is a priority for the company. However, there is no confirmed date, ticker, or exchange for the offering. Will the company sustain its 80 percent growth rate as it reaches a $200 billion valuation?
Customer growth and revenue scale
Databricks serves more than 20,000 organizations worldwide. This includes 70 percent of the Fortune 500. Many of these customers use the platform for data engineering and machine learning. Large companies like adidas, AT&T, Bayer, and Mastercard use Databricks. More than 500 customers spend more than $1 million annually with the company.
The company makes money through a consumption-based model. Customers pay based on the computing resources they use, which is measured in Databricks Units. This model allows revenue to grow as customers use more AI and data services. In the second quarter of 2026, the company exceeded a $7 billion revenue run rate. This is a massive scale for a private company.
The company sees high demand for its AI products. Customers are moving from "tokenmaxxing" to "valuemaxxing" to get better outcomes per dollar. This shift drives demand for the Unity AI Gateway and the Lakebase database. The company also sees growth in its newer verticals, including cybersecurity. The scale of its customer base provides a strong foundation for any future IPO.
The final assessment of Databricks
Databricks is currently a massive private entity that prioritizes capital from strategic investors over a public exit. The company is growing at 80 percent and has a $190 billion valuation. It is using its billions in new capital to dominate the AI agent and database market. The company is successfully building a product suite that addresses the needs of the largest enterprises.
The decision to stay private allows the company to invest in Lakebase and Genie without public scrutiny. It also helps the company manage the talent war by providing liquidity to employees through private rounds. The $190 billion valuation is a high price that depends on continued rapid growth. If the company slows down, that valuation will face pressure from the public market.
The company is clearly building a massive moat around its data and AI products. The scale of its revenue and its customer base makes it a dominant force in the industry. I believe the company will wait until the market is less crowded before it attempts to list. The $190 billion price tag is a signal that the company is prepared to go public on its own terms.
