LogicBlox’s mission is to simplify the way we store, process, analyze, and present data in order to build interactive and data intensive applications. The typical application infrastructure today involve a variety of specialized data storage systems, integrated together with ETL tools. The increasing interest in applying machine learning and prescriptive methods to data is adding even more tools — and more integration layers — into this infrastructure. Integration drives up fragility. Integration drives down developer productivity and application performance. LogicBlox tackles this problem from the database angle, by building a unifying database that is capable of handling a wide variety of query workloads: graph, multi-dimensional analytics, and transactional updates. For the right type of applications, LogicBlox can replace a number of specialized databases and the need to integrate them together. In this talk, we discuss some key insights and principles behind the LogicBlox database, as well as its relevance to the data science community.