Apache Hive is the top level project which was introduced by Facebook. Hive is SQL like query language tool which is known to perform similar function as MySQL, an approach based on Rational Databases (RDBMS). However, in real Hive provides bridging to RDBMS and feature of data warehousing, making it different from MySQL.
Hence, it is cleared that both the tools perform similar task, however the way to process makes them different to each other. Basic function of Hive is to provide an interface between the data stored and querying whereas, MySQL is used for online operations as it provides multiple read and write function. The tag line of HIVE is “schema on read”, which makes it differ from MySQL which follows the tag line as “schema on write”. According to DeRoos, (2014) Hive is based on idea of “write once and read many time” however, MySQL have notion as “Read and write many times”.
Hive is used in situations where the dataset is comparatively larger. However, if performance and frequent updating and modifying of data is the requirement then MySQL is good option. Hive is not made for manipulation at record level as the main aim of Hive is to provide analytics, whereas, MySQL is designed for easy manipulation of data at record level as well. Moreover, if scalability is concerned Hive provides cheaper option as compared to MySQL.
From the above discussion it is cleared that MySQL and Hive are two different tools having similar approaches but deal with different kinds of data in real time. Apart from this, Hive is not made for transactional approaches which MySQL are good at.