Bundle risk~$43B · lakehouse

Durable seat expansion — or will hyperscalers bundle the lakehouse away for free?

Net retention looks compounding until AI features land inside cloud contracts. Fisher quality vs Einhorn falsifier — pick before the mark moves.

Isolation seats: Philip Fisher · Peter Lynch · David Einhorn

Kill-shot Databricks

Logged in → Analyze pre-filled. Guest → register, then same desk. Not a buy button.

Why it is on the desk

Databricks is the data-platform compounder private markets still bid. Value asks about net retention; debate asks whether hyperscalers bundle the category away.

Committee angle

SaaS quality vs. cyclical IT spend. The falsifier is seat compression when AI features get bundled into cloud contracts.

Risks to watch

Cloud vendor bundling, open-source substitution, and late-cycle IT budget cuts.

Cached fact card

Secondary mark: ~$43B secondary (2024)
Last round: Tender / secondary
Revenue run-rate: $2.4B est.
Listed comparables: SNOW, MSFT, GOOGL

Private desk: secondary marks and public disclosures only. Not EDGAR. Not a live quote. Not investable price.

Prompt: "Research Databricks as a private company — lakehouse retention vs cloud bundling and secondary marks. No EDGAR."