It comes with several built-in analytics functions, such as k-means observations and k-means clustering, and enables users to apply sophisticated in-memory analytics using SQL-like queries. Presto in-memory analytics combines with Terracotta’s BigMemory capacity to enhance its capacity to scale hundreds of terabytes of data to meet the biggest real-time analytics requirements. Presto’s in-memory analytics is capable of processing hundreds of terabytes of data in a fraction of the time required by traditional methods.