Big data and analytics have been receiving attention for a few years, but many long-standing customers are unclear about how to move from traditional databases to modern concepts of data analytics. These customers worry about practical situations of lack of available skills in deploying modern infrastructure with compatibility to original systems, difficulties finding approaches to processing large-scale data, and other concerns make data analytics jobs slow and sometimes painful. Most of today’s general-purpose relational databases (e.g., Oracle, Microsoft SQL Server) originated as OLTP systems. Their shared-disk or shared-everything architectures are optimized for high-transaction rates at the expense of analytical query performance and concurrency.