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Brief
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Databricks Data Intelligence Platform

Databricks unifies data, analytics, and AI on a single open platform, enabling enterprises to eliminate data silos and operationalize intelligence at scale without vendor lock-in.

San Francisco, California, United StatesFounded 2013Parent: Databricks

Last updated May 11, 2026 by ATDb automated enrichment

Industry
Data & AI Infrastructure / AdTech Data Platform
Business Model
SaaS / Cloud Platform (Usage-based)
Target Market
Enterprise
Employee Count
5001-10000
Funding
$3.9B+
Revenue Range
$1.5B - $2B ARR
Parent Company
Databricks
API Available
Yes
Market Position

Leader in cloud data and AI platforms; primary open lakehouse alternative to Snowflake, widely adopted as foundational infrastructure in AdTech data stacks

Overview

Databricks is a leading data and AI company founded by the creators of Apache Spark, Delta Lake, and MLflow. Its Data Intelligence Platform — the current umbrella brand replacing the older 'Lakehouse Platform' framing — unifies data engineering, data warehousing, streaming, machine learning, and generative AI capabilities on a single, open architecture. The platform is built on Delta Lake and leverages a lakehouse paradigm that combines the flexibility of data lakes with the performance and reliability of data warehouses. In the AdTech and marketing data ecosystem, Databricks is widely used for large-scale audience data processing, identity resolution, customer data platform (CDP) workloads, attribution modeling, and real-time bidding analytics. Its ability to handle petabyte-scale data with low latency makes it a preferred infrastructure layer for ad networks, DSPs, SSPs, and data clean rooms. The platform's Unity Catalog provides fine-grained data governance, which is increasingly critical as privacy regulations reshape how advertising data is managed and shared. Databricks competes directly with Snowflake in the cloud data platform space and with hyperscalers like Google BigQuery and AWS Redshift. It has achieved unicorn-plus status with a valuation exceeding $43 billion as of its most recent funding rounds, and reported over $1.6 billion in annualized revenue in 2024. Its open-source roots and strong ecosystem of integrations — including with major cloud providers, BI tools, and AdTech platforms — have made it a foundational layer for modern data-driven advertising operations.

Products & Features

Delta Lake

Open-source storage layer providing ACID transactions, scalable metadata handling, and unified batch/streaming data processing

Databricks SQL

Serverless SQL analytics engine optimized for BI and ad-hoc querying on lakehouse data

MLflow

Open-source ML lifecycle management platform for experiment tracking, model registry, and deployment

Unity Catalog

Unified data governance and cataloging solution providing fine-grained access control, lineage, and compliance across all data assets

Databricks AutoML

Automated machine learning tool that helps data teams quickly build and deploy predictive models

Databricks Workflows

Orchestration service for scheduling and managing multi-task data and ML pipelines

Mosaic AI

Suite of tools for building, fine-tuning, and deploying large language models and generative AI applications

Delta Sharing

Open protocol for secure, real-time data sharing across organizations and cloud platforms without data movement

Databricks Marketplace

Data and AI marketplace for discovering, sharing, and monetizing data products and models

Photon Engine

High-performance native vectorized query engine that accelerates SQL and DataFrame workloads on Delta Lake

Key Features
Unified lakehouse architecture combining data lake flexibility with warehouse reliabilityMulti-cloud support (AWS, Azure, GCP)Real-time and batch data processing on a single platformBuilt-in MLOps and generative AI toolingUnity Catalog for unified governance and data lineageOpen-source foundation (Apache Spark, Delta Lake, MLflow)Serverless compute options for SQL and notebooksDelta Sharing for cross-organization data collaborationNative support for structured, semi-structured, and unstructured dataAuto-scaling and serverless infrastructure
Use Cases
Audience segmentation and activation at petabyte scaleCustomer 360 and identity resolution for advertisingAttribution modeling and marketing mix modeling (MMM)Real-time bidding log analysis and campaign performance analyticsData clean room implementation for privacy-safe collaborationPredictive LTV and churn modeling for ad-supported businessesETL/ELT pipelines for consolidating ad platform dataProgrammatic advertising data lake managementGenerative AI applications for ad creative and personalizationRegulatory compliance and data governance for GDPR/CCPA
Customer Segments
Large enterprises with complex data and AI needsAdTech platforms (DSPs, SSPs, ad networks)Retail media networksFinancial services and insuranceHealthcare and life sciencesMedia and entertainment companiesTelecommunicationsData-driven SaaS companies
Corporate history
  • 2013Founded
See integrations with Databricks Data Intelligence Platform (13)

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