Company Intelligence
Databricks is a data intelligence platform built on an open lakehouse architecture that unifies data warehousing and data lake functionality. Founded by the creators of Apache Spark, the company offers a comprehensive platform for data engineering, data science, machine learning, and analytics. Databricks' acquisition of MosaicML in 2023 gave it proprietary large language model training capabilities, and its Unity Catalog provides unified data governance across the lakehouse. The company is one of the most valuable private enterprise software companies globally.
Data & Analytics
Headquarters
San Francisco, CA
Employees
~7,000
Revenue
~$2.4B (estimated ARR, 2024)
Fiscal Year End
January 31
Founded
2013
Current leadership team based on public filings and announcements.
Ali Ghodsi
Co-Founder & CEO
Dave Conte
CFO
Matei Zaharia
Co-Founder & CTO
Naveen Rao
VP of AI (former MosaicML CEO)
Adam Conway
SVP of Product
Key events and changes that sales teams should know about.
Raised $10 billion at a $62 billion valuation from investors including Thrive Capital, Andreessen Horowitz, and T. Rowe Price -- one of the largest private funding rounds in tech history.
2024-12
Expanded Unity Catalog into an open-source universal data governance framework, enabling customers to manage data access, lineage, and quality across Databricks and non-Databricks environments.
2024-10
Deepened MosaicML integration with DBRX foundation model and custom model training capabilities, positioning the lakehouse as a complete AI development platform from data to deployed models.
2024-09
Launched Databricks Mosaic AI, combining MosaicML's model training with Databricks' data platform to offer end-to-end generative AI development, fine-tuning, and deployment on customer data.
2024-06
Grew headcount to ~7,000 with aggressive hiring across enterprise sales, AI/ML engineering, and customer success, reflecting strong demand and the $62B valuation expectations.
2024-08
Databricks sits at the center of the modern data stack, competing directly with Snowflake for the enterprise data platform market. The lakehouse architecture -- which combines the reliability of data warehouses with the flexibility of data lakes -- has gained significant enterprise traction, particularly among data engineering and data science teams. This positioning means Databricks customers are also buying complementary tools for data integration (Fivetran, Airbyte), orchestration (Airflow, Dagster), and visualization (Tableau, Looker), creating a rich ecosystem for vendors.
The company's AI strategy is more aggressive than most data platforms. Through the MosaicML acquisition and DBRX foundation model, Databricks isn't just providing infrastructure for AI -- it's building the models themselves. Mosaic AI enables customers to train custom LLMs and fine-tune foundation models directly on their lakehouse data. This appeals to enterprises that want to own their AI models rather than depending on OpenAI or Anthropic, creating procurement opportunities for GPU compute, model evaluation, AI safety, and MLOps vendors.
At a $62B valuation with ~$2.4B in ARR, Databricks operates at a premium that demands aggressive growth. The company employs ~7,000 people and is actively expanding its enterprise sales organization, particularly in regulated industries like financial services, healthcare, and government. Databricks uses a fiscal year ending January 31, similar to Salesforce. As a private company, procurement decisions can move faster than at public companies, but technical evaluations are rigorous -- data engineers and platform teams heavily influence buying decisions.
Key competitors based on market analysis and public filings.
Databricks' annual recurring revenue (ARR) is estimated at approximately $2.4 billion as of late 2024, growing at roughly 50% year-over-year. As a private company, Databricks does not publicly disclose detailed financials, but the company has stated it is growing rapidly and approaching profitability. The $62B valuation implies investors expect significant continued growth.
No, Databricks remains private as of early 2025. The company raised $10 billion at a $62 billion valuation in December 2024, one of the largest private funding rounds ever. While IPO speculation has been persistent, Databricks has not announced a specific timeline. The large funding round may delay IPO plans by providing substantial operational runway.
Databricks was co-founded in 2013 by seven academics from UC Berkeley's AMPLab who created Apache Spark: Ali Ghodsi (CEO), Matei Zaharia (CTO), Reynold Xin, Patrick Wendell, Andy Konwinski, Ion Stoica, and Arsalan Tavakoli-Shiraji. The deep academic roots in distributed computing and data systems remain central to the company's technical culture.
The Databricks lakehouse is an open data architecture that combines the best features of data warehouses (reliability, governance, performance) with data lakes (flexibility, low cost, support for diverse data types). Built on open standards like Delta Lake, Apache Spark, and Unity Catalog, the lakehouse eliminates the need to maintain separate data warehouse and data lake systems, reducing complexity and cost for enterprises.
Databricks and Snowflake are the two dominant modern data platforms, but they approach the market differently. Databricks originated from the data engineering and data science community with its lakehouse architecture, while Snowflake started as a cloud data warehouse for analytics and BI. Databricks has stronger AI/ML capabilities (MosaicML, custom model training), while Snowflake has traditionally been stronger in SQL analytics. Both are converging toward comprehensive data platforms.
See leadership changes, strategic initiatives, earnings insights, and buying signals for Databricks — updated continuously.
