Databricks vs Palantir: Revenue, Profit and Business Model
Databricks reported $7B of revenue in FY2026 and — of net income. Palantir reported $4.5B of revenue in FY2025 and $1.6B of net income.
Latest financial snapshot
Databricks
- Latest revenue
- $7B (FY2026)
- Net income
- —
- Net margin
- 0.0%
- Revenue growth
- +109.2% a year, FY2024–FY2026
Palantir
- Latest revenue
- $4.5B (FY2025)
- Net income
- $1.6B
- Net margin
- 36.3%
- Revenue growth
- +33.4% a year, FY2018–FY2025
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).
Palantir
Palantir lost money for most of its history: it reported a $1.17 billion net loss in 2020, the year it listed. It first reached GAAP profitability in Q4 2022 and has been profitable every year since: $209.8 million net income in 2023, $462.2 million in 2024 and $1.625 billion in 2025. In Q2 2026, revenue of $1.935 billion produced a 62% adjusted operating margin and $1.22 billion of adjusted free cash flow, and the company held $9.2 billion of cash and short-term Treasuries. Full-year 2026 guidance calls for $4.5-$4.7 billion of adjusted free cash flow.
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 |
Palantir
| Year | Revenue | Net income | Margin | Growth | Source |
|---|---|---|---|---|---|
| FY2025 | $4.5B | $1.6B | 36.3% | +56.2% | Source |
| FY2024 | $2.9B | $462.2M | 16.1% | +28.8% | Source |
| FY2023 | $2.2B | $209.8M | 9.4% | +16.7% | Source |
| FY2022 | $1.9B | -$373.7M | -19.6% | +23.6% | Source |
| FY2021 | $1.5B | -$520.4M | -33.7% | +41.1% | Source |
| FY2020 | $1.1B | -$1.2B | -106.7% | +47.2% | Source |
| FY2019 | $742.6M | -$579.6M | -78.1% | +24.7% | Source |
| FY2018 | $595.4M | -$580M | -97.4% | — | 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.
Palantir
- Government
51% (Q2 2026: $990M)
Software for U.S. and allied defense, intelligence and civil agencies. U.S. government revenue was $809 million in Q2 2026, up 90%.
- Commercial
49% (Q2 2026: $945M)
Foundry and AIP for enterprises. U.S. commercial revenue was $764 million in Q2 2026, up 149%.
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).
Palantir
How it makes money
Palantir earns money by licensing and hosting four software platforms under multi-year contracts. Gotham serves defense and intelligence agencies; Foundry integrates operational data for companies; Apollo deploys and updates software across cloud, on-premise and classified environments; and AIP connects large language models to customer data through Palantir's Ontology.
Growth strategy
Palantir's growth plan rests on three things: AIP bootcamps that turn pilots into production contracts in days, larger defense programs (Maven Smart System, TITAN, Army enterprise agreements), and expansion within existing customers. U.S. commercial customer count rose to 653 in Q2 2026, up 35% year over year, and total customers reached 1,049.
Competitive advantage
Palantir's edge combines security accreditation, entrenched deployments and the Ontology data model. Its software is accredited for classified U.S. government work, which new entrants spend years trying to earn. Programs such as the Army's TITAN ground station ($178.4 million award in 2024) and the Maven Smart System put Palantir deep inside military workflows, which raises switching costs.
Questions about Databricks vs Palantir
Which company has higher revenue — Databricks, Inc. or Palantir Technologies Inc.?
Databricks, Inc. reported $7.0B (FY2026), while Palantir Technologies Inc. reported $4.5B (FY2025). By last reported revenue, Databricks, Inc. is the larger business, with Palantir Technologies Inc. reporting a smaller revenue base. Note: these are from different fiscal years and are not a direct like-for-like comparison.
What is the market cap of Databricks, Inc. vs Palantir Technologies Inc.?
Palantir Technologies Inc. has a market capitalisation of $447.0B. A public market cap figure for Databricks, Inc. was not available (it may be privately held).
Which is more financially efficient — Databricks, Inc. or Palantir Technologies Inc.?
Databricks, Inc. generates $500k / employee in revenue per employee, while Palantir Technologies Inc. generates $1.01M / employee. Palantir Technologies 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 Palantir Technologies Inc. make money?
Databricks, Inc. and Palantir Technologies 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). Palantir Technologies Inc.: Palantir earns money by licensing and hosting four software platforms under multi-year contracts.
Is Databricks, Inc. bigger than Palantir Technologies Inc.?
By last reported revenue, Databricks, Inc. ($7.0B (FY2026)) is the larger company compared to Palantir Technologies Inc. ($4.5B (FY2025)). 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 Palantir overview