In Memory Computing: The Big Picture By Markus Kett

Modern software systems must process tons of data and must provide low latency responsiveness to be able to compete. We've known for a long time that traditional databases cannot keep pace. In-memory computing is incredibly faster. Therefore, in-memory concepts have been added at every nook and cranny. However, is it enough just to use some in-memory computing? Are there differences? Is it sufficient to simply use a cache? Are there pitfalls? When should I use a distributed cache? Is an in-memory database the better approach? What is actually an in-memory data grid? In this session, you learn the basics and get a better overview to make a decision that fits your project and team. MARKUS KETT Markus and his team are working on the open-source projects EclipseStore, Eclipse Serializer, and RapidClipse, which is a free Eclipse IDE distribution and visual Java IDE, and are contributors to the popular microservice frameworks Helidon and Micronaut. He is the editor-in-chief of the free JAVAPRO magazine in Germany, the founder and co-organizer of the Java conference series JCON, and co-founder and CEO of MicroStream. He is an independent editor for various developer magazines, and a speaker at numerous developer conferences, and user groups.