Databricks vs Snowflake: Revenue, Profit and Business Model
Databricks reported $7B of revenue in FY2026 and — of net income. Snowflake reported $4.7B of revenue in FY2026 and a net loss of $1.3B.
Latest financial snapshot
Databricks
- Latest revenue
- $7B (FY2026)
- Net income
- —
- Net margin
- 0.0%
- Revenue growth
- +109.2% a year, FY2024–FY2026
Snowflake
- Latest revenue
- $4.7B (FY2026)
- Net income
- -$1.3B
- Net margin
- -28.4%
- Revenue growth
- +74.1% a year, FY2019–FY2026
Financial summary
Databricks
Databricks does not publish audited financial statements because it is private, but it discloses key metrics with each funding round. Revenue for the fiscal year ended January 31, 2024 topped $1.6 billion. The revenue run-rate reached $5.4 billion in Q4 FY2026 (growth above 65%) and passed $7 billion in Q2 FY2027, the quarter ended July 31, 2026, with growth above 80%. Net retention has been reported above 140%, and the company says adjusted free cash flow has been positive over the trailing 12 months. Within that total, the Lakehouse data warehousing product passed a $1.5 billion run-rate, growing more than 100%, and Lakebase passed $100 million. More than 1,000 customers consume at over $1 million a year and more than 100 at over $10 million. Valuation rose from $62 billion (December 2024) to more than $100 billion (2025), $134 billion (February 2026), and $190 billion (August 2026).
Snowflake
Snowflake has grown from $96.7M of revenue in fiscal 2019 to $4.684B in fiscal 2026 while remaining GAAP unprofitable, largely because of heavy stock-based compensation. FY2026 revenue grew 29% and the GAAP net loss was $1.332B. Growth accelerated in fiscal 2027: Q2 revenue was $1.55B (+35%), product revenue $1.49B (+37%, the third straight quarter of acceleration), net revenue retention 126%, and non-GAAP operating margin 15.3%. GAAP operating loss for the quarter was $263M. On September 28, 2026 the company announced a $3.5B offering of 0.00% convertible senior notes due 2029 and 2031.
Revenue and profit by year
Databricks
| Year | Revenue | Net income | Margin | Growth | Source |
|---|---|---|---|---|---|
| FY2026 | $7B | — | 0.0% | +169.2% | Source |
| FY2025 | $2.6B | — | 0.0% | +62.5% | Source |
| FY2024 | $1.6B | — | 0.0% | — | Source |
Snowflake
| Year | Revenue | Net income | Margin | Growth | Source |
|---|---|---|---|---|---|
| FY2026 | $4.7B | -$1.3B | -28.4% | +29.2% | Source |
| FY2025 | $3.6B | -$1.3B | -35.5% | +29.2% | Source |
| FY2024 | $2.8B | -$836.1M | -29.8% | +35.9% | Source |
| FY2023 | $2.1B | -$796.7M | -38.6% | +69.4% | Source |
| FY2022 | $1.2B | -$679.9M | -55.8% | +106.0% | Source |
| FY2021 | $592M | -$539.1M | -91.1% | +123.6% | Source |
| FY2020 | $264.7M | -$348.5M | -131.6% | +173.9% | Source |
| FY2019 | $96.7M | -$178M | -184.2% | — | Source |
Where the revenue comes from
Databricks
- Data Engineering & Streaming (Lakeflow, Spark)
Not disclosed
DBU consumption for batch and streaming pipelines, ingestion, and transformation jobs.
- Lakehouse Data Warehousing (Databricks SQL)
Run-rate above $1.5B (Aug 2026)
Serverless SQL warehousing and BI queries on open-format data; Databricks says this line is growing over 100% year over year.
- AI, Agents & Model Serving (Mosaic AI, Agent Bricks, Genie)
Not disclosed
Consumption from model training and fine-tuning, vector search, model serving, and AI agents.
- Lakebase Operational Database
Run-rate above $100M (Aug 2026)
Serverless Postgres usage by applications and AI agents.
Snowflake
- Product Revenue (Compute, Storage, Data Transfer)~96%
Usage-based revenue from customers consuming Snowflake compute, storage and data transfer, including AI and data engineering services. Product revenue was $1.49B of $1.55B total in Q2 fiscal 2027.
- Professional Services and Other~4%
Consulting, onboarding and training services that help enterprise customers deploy and migrate workloads to the platform.
Business model and strategy
Databricks
How it makes money
Databricks makes money by charging for compute consumed on its platform, measured in Databricks Units (DBUs). Customers usually sign annual or multi-year committed-spend contracts and then draw them down as their engineers run pipelines, SQL queries, model training, model serving, and AI agents. There is no flat seat fee for most workloads, so revenue rises as data volumes and AI usage grow.
Growth strategy
Databricks is expanding from analytics into the systems that enterprise AI agents run on. The 2026 funding is earmarked for three products: Lakebase, a serverless Postgres database for agents built on the 2025 acquisition of Neon; Genie, an AI coworker that answers business questions from governed data; and Unity AI Gateway, which routes requests across AI models with governance and cost controls.
Competitive advantage
Databricks' absolute competitive advantage is its foundational connection to the open-source community, specifically 'Apache Spark'. The founders of Databricks literally invented Apache Spark (the large, open-source data processing engine used by nearly every tech company on earth).
Snowflake
How it makes money
Snowflake runs a consumption-based cloud data platform on top of AWS, Microsoft Azure and Google Cloud. Customers are billed for compute (virtual warehouses, Snowpark, Cortex AI and other services, metered in credits), for storage per terabyte per month, and for data transfer. Most large customers sign multi-year capacity commitments and draw them down as they use the platform;
Growth strategy
Under CEO Sridhar Ramaswamy, Snowflake is positioning itself as the data layer for enterprise AI agents. It is adding AI services (Cortex AI, Cortex Agents and Snowflake Intelligence), developer tools (Snowpark, Streamlit, Snowflake Postgres) and open-format support (Apache Iceberg).
Competitive advantage
Snowflake's main advantages are that it runs the same platform across AWS, Azure and Google Cloud, which reduces lock-in to a single hyperscaler, and that storage and compute scale independently, so customers pay only for compute while it runs. Secure data sharing and the Snowflake Marketplace let separate organizations query the same live data without copying it, which creates network effects.
Questions about Databricks vs Snowflake
Which company has higher revenue — Databricks, Inc. or Snowflake Inc.?
Databricks, Inc. reported $7.0B (FY2026), while Snowflake Inc. reported $4.7B (FY2026). By last reported revenue, Databricks, Inc. is the larger business, with Snowflake Inc. reporting a smaller revenue base.
What is the market cap of Databricks, Inc. vs Snowflake Inc.?
Snowflake Inc. has a market capitalisation of $118.0B. A public market cap figure for Databricks, Inc. was not available (it may be privately held).
Which is more financially efficient — Databricks, Inc. or Snowflake Inc.?
Databricks, Inc. generates $500k / employee in revenue per employee, while Snowflake Inc. generates $517k / employee. Snowflake Inc. shows higher revenue efficiency per headcount, though this reflects business model differences — capital-light software companies routinely outperform labour-intensive manufacturers on this metric.
How do Databricks, Inc. and Snowflake Inc. make money?
Databricks, Inc. and Snowflake Inc. generate revenue in fundamentally different ways. Databricks, Inc.: Databricks makes money by charging for compute consumed on its platform, measured in Databricks Units (DBUs). Snowflake Inc.: Snowflake runs a consumption-based cloud data platform on top of AWS, Microsoft Azure and Google Cloud.
Is Databricks, Inc. bigger than Snowflake Inc.?
By last reported revenue, Databricks, Inc. ($7.0B (FY2026)) is the larger company compared to Snowflake Inc. ($4.7B (FY2026)). Revenue scale is one dimension of size — market capitalisation, employee count, and geographic reach are also relevant depending on the context.
Figures come from each company's filings and the sources linked beside them. Amounts reported in another currency are shown in US dollars at an approximate rate and marked with ~. Back to the Databricks vs Snowflake overview