Today, data is growing at an exponential rate, and the need to analyze and execute queries in near real time on petabytes of data has pushed OLAP (Online Analytical Processing) engines to evolve well beyond their batch-oriented origins. Historically, OLAP systems were designed to process large datasets in batch mode, with efficient query execution treated as a secondary concern. Modern workloads, however, increasingly demand that OLAP engines behave more like OLTP (Online Tra

Today's distributed systems are undoubtedly complex and varied, requiring different data consistency guarantees. Amongst all,...

Data is exploding exponentially and so is the requirement for massively scalable distributed storage systems. A distributed storage...