The ROADRUNNER project aims to directly address the shortcoming of existing state of the art techniques for both efficient and scalable data analytics, by introducing various optimizations to MapReduce processing, thus enhancing its functionality and improving its performance. In essence, ROADRUNNER intends to propose a new framework for large-scale analysis of Big Data that builds on successful ideas originating from the MapReduce model (scalability) coupled with appropriately adjusted established techniques for query processing and optimization known for decades in the parallel data management community (efficiency).