Databricks
Databricks is a data and AI company headquartered in San Francisco whose core platform is built on an open lakehouse architecture, providing a unified foundation for data storage, governance, and AI.
Last updated Oct 11, 2026 by the ATDb Editorial Team
AI-drafted from public sources59 sources cited
At a glance
- Employees
- 5001-10000
- Funding
- $4.4B+
- Revenue
- $1.5B–$2B ARR (estimated)
- Stock
- NYSE:DB
About
Market leader in unified data lakehouse platforms; top-tier competitor to Snowflake and cloud-native data services from AWS, Google, and Microsoft
Databricks is a data and AI company headquartered in San Francisco whose core platform is built on an open lakehouse architecture, providing a unified foundation for data storage, governance, and AI. For advertising and marketing use cases, the platform enables teams to consolidate campaign data from sources such as ad platforms, CRMs, and web analytics tools into a centralized warehouse, with the goal of delivering real-time visibility into attribution, funnel conversion, and ROI across channels. It supports advanced marketing analytics including attribution modeling, customer lifetime value prediction, and churn forecasting, with native support for Python, R, and Scala so data science teams can build custom models directly on marketing data. In the adTech space specifically, Databricks has been adopted for its streaming capabilities, enabling real-time ad performance dashboards for advertisers and their clients, while also delivering cost savings over legacy data platforms. More than 20,000 organizations worldwide, including 70% of the Fortune 500, rely on the Databricks platform. Source 1: databricks.com — About Databricks: The data and AI company Source 2: improvado.io — Databricks Analytics Guide: How Marketing Teams Use It Source 3: aimpointdigital.com — Building Application Streaming for Real-Time Ad Metrics ...
Business model
SaaS / Usage-based Cloud Platform
Target market
Enterprise
What they offer
Databricks Lakehouse Platform
Unified platform combining data lake flexibility with data warehouse performance, built on Delta Lake and Apache Spark
Delta Lake
Open-source storage layer that brings ACID transactions, scalable metadata handling, and unified streaming/batch data processing
MLflow
Open-source platform for managing the end-to-end machine learning lifecycle including experimentation, reproducibility, and deployment
Databricks SQL
Serverless SQL analytics engine optimized for BI and ad-hoc querying on the lakehouse
AutoML
Automated machine learning capability that helps data scientists quickly build and deploy models with minimal manual effort
Delta Sharing
Open protocol for secure, governed data sharing across organizations and cloud platforms without data movement
Unity Catalog
Unified governance solution for data and AI assets across the lakehouse, providing fine-grained access control and lineage
Databricks Workflows
Fully managed orchestration service for building and scheduling multi-task data and ML pipelines
Mosaic AI
Suite of tools for building, fine-tuning, and deploying large language models and generative AI applications
Databricks Marketplace
Open marketplace for discovering and sharing data, analytics, and AI assets across the ecosystem
Key features
Use cases
Customer segments
Tech & specs
Technology stack
Security & compliance
Deployment
API
Yes