How did you outmaneuver Snowflake, a company that had double your revenue?

We studied their weaknesses carefully. Three stood out. First, their stack was fully proprietary. The data sat in their format and customers were worried about lock-in. Second, their AI and machine learning story was weak. Third, they were expensive. We went after all three simultaneously. We positioned Databricks around the open lakehouse, meaning you own your data in open formats, you can do AI on it natively, and the total cost of ownership is about a third of the alternative. We also ran a coexistence strategy rather than a rip-and-replace message. We would go into accounts and identify the specific workloads suited to machine learning, pull those out, and move them to open formats. It was a very precise playbook executed account by account. That strategy took about four years to play out. You cannot do something like that overnight.