Databricks pitches LTAP as a new foundation for agentic applications (opens in new tab)

As enterprises rush to build AI agents that can reason over business data and take action, Databricks argues that the long-standing practice of separating operational and analytical data systems is turning into a liability. That separation, the cloud-based data warehouse provider says, is becoming increasingly strained as AI agents require simultaneous access to live operational data and historical context to make decisions and take actions in real time, unlike humans, who traditionally can w...