Google Analytics' launch was a disaster due to its high hardware requirements, but it eventually became a highly profitable product. The key to Google's success lay in allowing customers to segment and calculate flexible aggregates using raw unaggregated data. Most companies have built analytics with precomputed data due to cost and technology constraints. SingleStore is changing this conventional wisdom by offering companies the ability to serve raw unaggregated data performance to a range of customers. This is achieved through scale-out, columnstore query execution, and efficient data isolation per customer. Scale-out allows for distributed systems with dedicated compute power to meet demand, while columnstore query execution enables simple queries to run at hundreds of millions to over a billion data points per second per core. Efficient data isolation per customer ensures that only scanned data belongs to a single customer, allowing high concurrency and fast response times. SingleStore's innovations in query processing capabilities enable sub-second performance for complex queries on large datasets.