Big data involves processing massive amounts of diverse information and delivering insights rapidly—often summed up by the four V's: volume, variety, velocity, and veracity. Data scientists and analysts need dedicated tools to help turn this raw information into actionable content, a potentially overwhelming task. Fortunately, some effective tools exist to make the task easier. Hadoop is one of the most popular software frameworks designed to process and store Big Data information. Hive, in turn, is a tool designed for use with Hadoop. This article details the role of Hive in big data, as well as details such as Hive architecture and optimization techniques. Let’s start by understanding what Hive is in Hadoop. What is Hive in Hadoop? No one can better explain what Hive in Hadoop is than the creators of Hive themselves: "The Apache Hive™ data warehouse software facilitates reading, writing, and managing large datasets residi...