Data properties and hardware characteristics are two key aspects for efficient data management. A clear trend in the first aspect, data properties, is the increasing demand to manage and process Big Data in both enterprise and consumer applications, characterized by the fast evolution of “Big Data Systems”. Examples of big data systems include NoSQL storage systems, MapReduce/Hadoop, data analytics platforms, search and indexing platforms, messaging infrastructures, event log processing systems, as well as novel extensions to relational database systems. These systems address needs for processing structured, semi-structured, and unstructured data across a wide spectrum of domains such as web, social networks, enterprise, mobile computing, sensor networks, multimedia/streaming, cyber-physical and high performance systems, and for a great many application areas such as e-commerce, finance, healthcare, transportation, telecommunication, and scientific computing. At the same time, the second aspect, hardware characteristics, is undergoing rapid changes, imposing new challenges for the efficient utilization of hardware resources. Recent trends include massive multi-core processing systems, high performance co-processors, very large main memory systems, storage-class memory, fast networking components, big computing clusters, and large data centers that consume massive amounts of energy. Utilizing new hardware technologies for efficient Big Data management is of urgent importance. However, many essential issues in this area have yet to be explored, including system architecture, data storage, indexes, query processing, energy efficiency and proportionality. The aim of this half-day workshop is to bring together researchers, practitioners, system administrators, and others interested in this area to share their perspectives on the efficient management of big data over new hardware platforms, and to discuss and identify future directions and challenges in this area.