Apps produce data, lots of it. Apps and microservices in particular consume a very specific part of my data cake and never quite in the form I expect it to. Data must be squeezed to analyse the crap out of it. And it would be nice if all of this was fast! In memory data systems like Infinispan can help you with that. Come discuss architectures and situations where an in-memory system helps. We will dive in particular to the spectrum of query capabilities from directly running classic queries, full-text and spatial queries (Lucene), Map/Reduce, continuous query, generic code execution and even Hadoop and Spark. Emmanuel Bernard is data platform architect for the JBoss portfolio at Red Hat getting his open source hands in Hibernate, Infinispan, Debezium and more. He had founded and lead Hibernate Search, Validator and OGM and participated to the Bean Validation spec (as lead) and the JPA one (as expert). Nowadays his focus revolves around NoSQL, analytics and streams of data. He is the founder and co-host of two podcasts: JBoss Community Asylum (English) and Les Cast Codeurs Podcast (French). [CSP-1623]