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.

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.

Products by Databricks

Databricks Mosaic AI

Build, serve, and govern models and agents directly on the Databricks lakehouse.

Strategic Product Influence — Editorial 85/100 · version not recorded

Data AI PlatformDatabricks

Score methodology

Latest coverage

SNOW vs. Databricks: The AI Data War Wall Street May Be UnderpricingMay 9, 2026

All Databricks coverage →

Why it matters

Databricks is the biggest test of whether AI-era software companies even need public markets — it raises billions at will, and Ghodsi has called a crowded listing year the worst time to IPO. It also carries the clearest evidence that enterprise AI spend is real rather than pilot-project theater: $1.4 billion of AI product revenue from customers building on their own data.

Core moat

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.

Risks

The sharpest risk is the valuation itself: at marks reported near $175 billion, Databricks is priced above thirty times its run rate, so any deceleration in enterprise AI budgets lands directly on the eventual IPO price — and it is fighting Snowflake plus every hyperscaler's native data stack for the same dollars.

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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.