A number of key technological, social, and business disruptions will drive a new generation of smarter energy applications. The disruptions include the following: 1) large sensor deployments, resulting in a huge increase in data volumes and variety, 2) a move toward clean energy and intermittent renewable energy sources, and 3) a move to highly distributed energy resources. To enable resilient and efficient power delivery, with these disruptions, will require a host of new applications that analyze large amounts and varieties of data in the context of the connected grid and perform analysis, visualization, and control in real-Time with very low latency. In this paper, we present a set of capabilities that enable such applications, and a software and hardware platform that combines these capabilities to enable rapid development of a wide array of high-performance and analytics-rich applications. These capabilities include: 1) high-performance time-series ingestion, 2) a flexible data model that spans multiple contexts, 3) high-performance, in-memory analysis of time-varying, hierarchical graphs, 4) data service for co-presenting real-Time and static spatiotemporal data for real-Time web-based visualization, and 5) a seamless combination of event-based and service-oriented programming models.