$4b in revenue run-rate. There are two data giants both now at this mark after Databricks announced it surpassed the threshold.
This is an opportunity to compare the two leading data companies at a revenue intersection.
Head-to-Head Comparison
| Metric | Databricks | Snowflake |
|---|---|---|
| Revenue Run Rate | $4.0B | $4.1B |
| $1M+ Customers | 650 | 654 |
| Net Dollar Retention | 140% | 125% |
| YoY Growth Rate | 50% | 28% |
| Valuation | $100B | $75.9B |
| Market Status | Private | Public |
| AI Revenue | $1B | Not disclosed |
Both are at $4b in revenue. Each claims over 650 customers paying $1M+ annually. Each boasts strong net dollar retention (140% vs 125%).
Databricks is growing at 50% compared to Snowflake’s 28% & in the private market trades at a premium for that growth rate. Snowflake has reaccelerated but it was about a year later than Databricks.
Comparing the valuation to revenue-run-rate shows Databricks is trading at a 35% premium to Snowflake.1
Databricks is valued at $100B privately while Snowflake trades at $75.9b publicly. In this market, every 1% of growth adds 0.3x to valuation multiple. Given Databricks’ 22-point growth advantage, the 35% premium may actually understate the true difference in ultimate business size.
This premium reflects the scarcity of high-growth data platforms in public markets. There really is no equivalent to Databricks today. Palantir at 39% growth trades at 75x forward (not run-rate). Rubrik, in the twilight of a transition from on-prem to cloud, trades at 15x forward on 44% growth.
The 35% valuation premium reflects both Databricks’ superior growth & the market’s bet on AI. With AI revenue already at $1B & driving concomitant compute demand, Databricks has positioned itself at the center of the most valuable trend in enterprise software.
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$100b/$4b = 25x vs $75.9b/$4.1b 18.5x ↩︎