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Compare up to four researched companies across market position, company facts, financial context, and classifications.
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Select companies in the slots below to reveal a useful side-by-side view. You can compare up to four companies and change any selection later.
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| Description | ||||
| 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 | |||
| Company type | Private | |||
| Pricing model | usage based | |||
| Last updated | Jun 21, 2026 | |||
| 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) | |||
| Segments & Industries | ||||
| 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 | |||
