Databricks

Research Team Data Published Compare

Summary

Unified data and AI platform for data engineering, analytics, ML, generative AI, agents, and governance.

Description

Databricks provides a unified lakehouse platform with ETL/Lakeflow, data warehousing, BI/Genie, Mosaic AI/Agent Bricks, model serving, AI Search/vector search for RAG, MLflow registry, and governance via Unity Catalog.

Positioning

Data Intelligence Platform for enterprise data, analytics, and AI

Key facts

HQ location
San Francisco, CA, USA
Founded
2013
Employee range
5001-10000
Funding stage
Company type
Private
Pricing model
Usage Based (Usage-based cloud platform)
Last updated

Financials

Revenue estimate
>$5.4B revenue run-rate (Feb 2026)
Valuation estimate
>$100B last confirmed; later secondary/talks may vary
Investments
Series K at >$100B valuation announced Aug 2025; prior multi-billion total funding

Relationships

Target customers
Enterprise data, analytics, ML engineering, and AI application teams
Key competitors
Snowflake, Palantir, DataRobot, Domino Data Lab, H2O.ai
Known customers
AT&T, Shell, Walgreens, Comcast, Condé Nast (public case studies/examples)

Classification (raw research text)

Core focus
Data and AI platform / lakehouse / enterprise AI
Core industry
Data & AI Infrastructure
Core category
Lakehouse and AI platform

Shown verbatim from the research spreadsheet — deriving structured industry tags from this text is a future phase.

Segments, Industries & Certifications

Segments

AI Workflows, AI Agents, LLM Fine-tuning, AI Developer Tools, Knowledge & RAG, Document AI, LLM Deployment, AI Quality & Observability, Traditional ML, AI Governance & Risk, Chatbots, Analytics & BI