Databricks company profile: valuation, funding & revenue

This Databricks company profile covers the company's valuation, revenue, funding rounds, investors and history. Databricks works in data and AI software, with a focus on data platform. It was founded in 2013 and is headquartered in San Francisco, California, United States. Its latest valuation on record is US$190 billion (August 2026). Every figure links to a public source, and anything the company hasn't disclosed is marked as such.

Revenue

More than US$7 billion annualized revenue run rate, growing over 80% year over year — Annualized revenue run rate (company-reported), as of August 2026. Source: Dealroom (reporting the announcement).

Funding history

Databricks timeline

Key dates from the sources on this page, oldest first. Metric snapshots are listed after the funding events.

• 2013 — Databricks is founded in San Francisco by Ali Ghodsi (CEO), Matei Zaharia, Ion Stoica and other co-founders.
• Aug 2025 — Series K: Not detailed in source, valuing the company at US$100B.
• Late 2025 — Series L: More than US$4B, valuing the company at US$134B. Investors: Insight Partners, Fidelity and J.P. Morgan Asset Management (leads).
• Aug 2026 — Equity round: US$5B, valuing the company at US$190B.
• Late 2025 — Revenue run rate (Q3 2025): More than US$4.8 billion, growing over 55% year over year.
• Late 2025 — Net retention: Above 140%.
• Late 2025 — Large customers: More than 700 customers at over US$1 million annual run rate.
• Late 2025 — Free cash flow: Positive over the trailing 12 months (company-reported).

Investors

Overview

Databricks makes a data and AI platform that large organizations use to store, process and analyse huge amounts of data, and increasingly to build and run AI applications on that data. It popularised the idea of the "lakehouse," which combines the cheap, flexible storage of a data lake with the reliability and performance of a traditional data warehouse. Companies use it for everything from financial reporting and fraud detection to training machine learning models and powering AI assistants.

Databricks was founded in 2013 by the creators of Apache Spark, an open-source data processing engine developed at the University of California, Berkeley. Ali Ghodsi is CEO, and his co-founders include Matei Zaharia, Spark's original creator, and Ion Stoica. Its open-source roots remain central to its strategy and reputation among engineers.

How Databricks makes money

Databricks charges mainly based on usage: customers pay for the computing resources they consume on its platform, usually through committed annual contracts. That means revenue grows as customers process more data and run more AI workloads, without needing to sell new licences. It's a powerful model when customers' data and AI usage is expanding quickly, which helps explain Databricks' very high net retention.

The company has added products around its core platform, including data warehousing (Databricks SQL), governance (Unity Catalog), AI model development and serving, and, more recently, an operational database product. Each new product gives customers another reason to run more of their data work on Databricks.

Revenue and growth

Unusually for a private company, Databricks discloses its revenue run rate at major funding events:

• About a year before late 2025: around US$3 billion run rate.
• Q3 2025: more than US$4.8 billion, growing over 55% year over year, with positive free cash flow over the previous 12 months, net retention above 140% and more than 700 customers each paying over US$1 million a year.
• August 2026: more than US$7 billion, with revenue growth above 80% year over year in the second quarter.

Growth that accelerates at this scale is rare. A large part of it is attributed to demand for AI: companies need clean, well-governed data before AI applications can work, and Databricks sits right at that point.

A net retention rate above 140% means existing customers, as a group, were spending more than 40% more each year. Our guide on net revenue retention explains why investors treat this as one of the strongest signals in software.

Funding history

Databricks has raised many rounds over its history. The most recent are:

• August 2025, Series K: a valuation of US$100 billion.
• Late 2025, Series L: more than US$4 billion at a US$134 billion valuation, led by Insight Partners, Fidelity and J.P. Morgan Asset Management.
• August 2026: US$5 billion at a US$190 billion valuation, less than a year after the Series L. The company said proceeds would go towards products including Lakebase, Genie and Unity AI Gateway.

The speed of these step-ups, from US$100 billion to US$190 billion in about a year, reflects both its accelerating growth and how highly investors value companies at the centre of enterprise AI spending.

Valuation in context

At US$190 billion against a run rate of just over US$7 billion, Databricks was valued at roughly 27 times run-rate revenue. That's high by the standards of mature software, but investors justify it with growth above 80%, positive free cash flow and very high net retention. Compare it with the multiples we calculate for companies on our Canadian unicorns page, and see our guide to building a comps list for how to use figures like these.

Competitive landscape

Databricks competes most directly with cloud data platforms, especially Snowflake, and with the data and AI services of the major cloud providers, which are also its partners, since Databricks runs on their infrastructure. Its strengths are its open-source heritage, its appeal to data engineers and data scientists, and its unified approach to data and AI. The main risks are intense competition from cloud providers, the cost of keeping pace in AI, and the possibility that AI spending slows after the current boom.

The IPO question

Databricks is widely expected to go public eventually, and its scale, growth and positive free cash flow would make it one of the largest software IPOs ever. So far, it has been able to raise very large private rounds instead, which gives it flexibility on timing. Its willingness to disclose revenue run rates suggests it is already operating with some of the transparency public investors expect.

What to watch next

Watch revenue run-rate updates, growth in its newer products such as its operational database and AI tools, competition with Snowflake and the cloud providers, acquisitions, and IPO timing.

Key facts at a glance

Databricks is a San Francisco data and AI platform company founded in 2013 by the creators of Apache Spark, led by CEO Ali Ghodsi. It was valued at US$100 billion in August 2025, US$134 billion in its late-2025 Series L led by Insight Partners, Fidelity and J.P. Morgan Asset Management, and US$190 billion in an August 2026 round of US$5 billion. It reported a revenue run rate above US$7 billion, growing more than 80% a year, net retention above 140% and positive free cash flow.

What this means if you're…

Choosing a data platform: compare total cost under your real workloads, governance features, AI capabilities and how well each option fits your team's skills.

Selling to Databricks customers: companies investing heavily in data platforms often buy complementary tools for data quality, integration, security and AI applications.

A SaaS founder: Databricks shows how usage-based pricing combined with expanding product scope can drive extraordinary net retention.

Latest developments (October 2026)

Databricks said in February 2026 that its annualised revenue run rate had passed US$5.4 billion, up 65% from a year earlier, according to reporting summarised by Dealroom, and its valuation climbed through successive rounds to US$190 billion in August 2026. It had not filed for an IPO by mid-2026, and investors were told a listing could come as soon as 2027. Databricks remains the most valuable private data and AI software company in our database.

Sources

Every figure on this page comes from the public sources below. Where sources disagreed, we used the company's own announcement or a primary news report. Private-company data changes; check the date beside each figure.

1. The Star (reporting the announcement)
2. Dealroom
3. Constellation Research