Databricks is trying to siphon off software-makers’ last moat. As it rapidly out-grows old-guard app-makers like Adobe and Salesforce, it’s using its prodigious funding to expand into their markets. The argument that old code will stick around, despite the appeal of replacing it with chatbot-generated alternatives, centers around these products being closely wedded to companies’ unique information. An AI-boosted data gatherer might disrupt that advantage, further cementing a massive shift in valuations.
The $188 billion valuation that Databricks won in a funding round announced last week represents about 27 times the $6.9 billion revenue run-rate it expects to reach in the first half of financial year 2027, according to figures from TD Cowen. That is more than double the multiple commanded by publicly traded rival Snowflake.
That gap makes some sense, given that Databricks is growing roughly twice as quickly as Snowflake. It’s also benefitting from the increasing concentration of private capital in a handful of AI leaders. Boss Ali Ghodsi is riding the chatbot wave by developing tools that gather and wrangle the vast reams of data involved.
Enterprise software vendors like Salesforce derive some of their power and profitability from sheer inertia. Their tools store and organize data that is crucial to day-to-day business functions. Despite the industry's median enterprise value as a multiple of trailing-twelve-month revenue nearly halving over the past year, the argument goes that this entanglement will make them hard to switch out.
AI might offer a countervailing push. So-called agents, or language models that can autonomously complete multi-step tasks, represent the most plausible path to profitable, labor-and-cost-saving advances from chatbot technology. To realize this value, they require unfettered access to data and tools from one centralized spot. Naturally, this moves the center of corporate gravity to platforms like Databricks.
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