Enterprise AI and Data Platform
Databricks
Databricks sells a lakehouse platform for enterprise data and AI, private at a $134B valuation and a $5.4B run rate.
Databricks built the lakehouse category — one platform where enterprises keep raw data, run analytics, and assemble AI systems through Mosaic AI — and now prices itself like the category winner. The numbers are no longer startup numbers: a $5.4 billion revenue run rate growing 65% a year, with AI products contributing $1.4 billion annualized. The structure still is: private, after a February raise of $5 billion at a $134 billion valuation, with mid-year talks reported at up to $175 billion while CEO Ali Ghodsi points at a possible 2027 listing.
Frequently asked about Databricks
- What does Databricks do?
- Databricks sells a lakehouse platform for enterprise data and AI, private at a $134B valuation and a $5.4B run rate.
- Is Databricks publicly traded?
- Databricks is a private company; its shares do not trade on a public exchange.
- When was Databricks founded and where is it based?
- Databricks was founded in 2013 and is headquartered in San Francisco, California.
- What products does Databricks make?
- Databricks's products in the TECHi Atlas: Databricks Mosaic AI.
- What is Databricks's competitive advantage?
- The moat is workload gravity: once petabytes and the pipelines that feed them live in a company's lakehouse, every new AI project defaults to being built there, and the governance layer makes leaving a compliance exercise rather than a migration. Open data formats soften the lock-in story — which is exactly why governance, not storage, is where Databricks digs in.
