When a new, superior technology paradigm emerges (e.g., cloud software), it doesn't just compete with the old one (on-premise). It grows the entire market by an order of magnitude. This principle suggests Databricks could be 10 times bigger than Oracle.
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Traditional valuation models assume growth decays over time. However, when a company at scale, like Databricks, begins to reaccelerate, it defies these models. This rare phenomenon signals an expanding market or competitive advantage, justifying massive valuation premiums that seem disconnected from public comps.
A16Z's investment thesis posits that platform shifts (e.g., on-prem to cloud) create companies 10x larger than the incumbents they replace. They applied this logic to Databricks (vs. Oracle) and Substack (vs. traditional media), arguing against conservative market sizing.
Investors must recognize that S-curve forecasts are not static. Whale Rock initially modeled cloud computing as a $300B deflationary market (versus $600B in traditional IT spend) but later realized it was a full $600B market as it spurred new demand, significantly extending the investment runway.
Databricks is raising massive rounds to build an AI offering that rivals cloud giants like AWS. This shifts the primary competitive landscape from a focused battle with Snowflake to a broader war for the enterprise AI agent market, explaining their aggressive fundraising and strategy.
Successful AI products like Gamma and Cursor don't just add a feature; they create so much value they can charge orders of magnitude more than legacy alternatives. This massive Total Addressable Market (TAM) expansion, not a simple price bump, is the engine of their explosive growth.
Traditional market sizing, which analyzes existing demand, is useless for true technological breakthroughs. A fundamental change on the supply side (e.g., GPUs for AI, cloud for software) unlocks markets that are orders of magnitude larger than their predecessors (e.g., gaming, on-prem software).
The current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.
The narrative of startups "destroying" incumbents is often wrong. As shown by MongoDB coexisting with Oracle and HubSpot with Salesforce, disruptive companies can create massive value by expanding the total market, allowing both new and old players to grow simultaneously.
Companies like Amazon (from books to cloud) and Intuitive Surgical (from one specific surgery to many) became massive winners by creating new markets, not just conquering existing ones. Investors should prioritize businesses with the innovative capacity to expand their TAM, as initial market sizes are often misleadingly small.
Investors err when they size a new market based on its predecessor (e.g., Uber vs. taxis). A fundamental supply-side change creates new capabilities that unlock massive, previously invisible demand, making initial market size calculations dangerously conservative.