In-Memory Computing uses distributed memory systems to process and analyze large datasets in real-time, which is orders of magnitude faster than disk-based systems. It has become practical due to declining memory prices and increasing data sizes. While some myths exist that it is too expensive, not durable, or only for databases, in reality in-memory computing is applied across different workloads and provides benefits like real-time analytics, logistics, and monitoring.