# Databricks

Data lakehouse software for managing, querying, and analyzing enterprise-scale AI and data workloads

## Key Financials

### Revenue
**$6.90B** (2026)

### Valuation
**$188.00B** (2026)

### Funding
**$15.00B** (2025)

### Growth Rate (y/y)
**50%** (2025)

### Details
- **Headquarters**: San Francisco, United States
- **CEO**: Ali Ghodsi
- **Website**: [databricks.com](https://www.databricks.com/)

## Milestones
### Founding Year
2013

## Revenue Metrics
| Time       | Metric                          | Measurement | Type       |
|------------|---------------------------------|-------------|------------|
| Feb 2026   | Annualized revenue (AI products)| $1.4B      | historical |
| 2026       | Annualized revenue growth       | —           | historical |
| Jan 2026   | Annualized revenue (Databricks SQL)| —       | projection  |
| 2025       | Annualized revenue growth       | —           | historical |
| Sep 2025   | ARR (AI products)              | —           | historical |

## Product Overview
[Databricks](/content/c/databricks/index.html)' Data Intelligence Platform combines data lake storage, data warehouse analytics, and machine learning in a single cloud-hosted environment.

- **Delta Lake**: An open-source storage layer providing reliability and performance with features like ACID transactions.
- **Mosaic AI**: Covers the machine learning lifecycle, from feature engineering to deployment and monitoring.
- **Lakebase**: A fully managed Postgres operational database layer designed for AI applications.
- **Agent Bricks**: Automates AI agent creation for enterprise use cases.

## Business Model
[Databricks](/content/c/databricks/index.html) operates a B2B, consumption-based SaaS model, charging customers based on compute, storage, and data processing usage.

## Competition
- **Snowflake**: Competes directly in the cloud analytics market.
- **Hyperscalers**: AWS, Azure, and Google Cloud offer integrated services that overlap with Databricks' offerings.
- **Specialized AI Platforms**: Emerging platforms challenging Databricks' position in machine learning and AI workloads.

## Risks
- **Hyperscaler Competition**: Dependence on AWS, Azure, and GCP for infrastructure.
- **AI Commoditization**: Rapid advancements in open-source AI could undermine proprietary offerings.
- **Implementation Complexity**: The need for significant technical expertise can limit market adoption.

## Recent News
- **July 24, 2026**: Databricks and Microsoft expanded partnership to enhance AI capabilities using Azure, improving efficiency for over 20,000 organizations.

## Filings
| Name                                   | Type                          | Filed At    |
|----------------------------------------|-------------------------------|-------------|
| databricks_coi_2025-12-16              | Certificate of Incorporation   | Dec 16, 2025 |
| databricks_coi_2025-09-08              | Certificate of Incorporation   | Sep 08, 2025 |
| databricks_coi_2024-12-17              | Certificate of Incorporation   | Dec 17, 2024 |