In the presentation, we will provide an overview of general in-memory computing principles and the drivers behind it. We will start with a summary of the technical drivers (abundant hardware resources) and market forces (the rise of Big Data). We will cover popular and emerging use cases for in-memory computing, from financial industry trading platforms to mobile payment processing, online advertising, online/mobile gaming back-ends and more. We will then present some foundational concepts and terminology, and discuss considerations around any in-memory solution. From there, we will illustrate how a complete in-memory computing stack like GridGain combines clustering, high performance computing, in-memory data grids, stream processing and Hadoop acceleration into one unified and easy to use platform.