At the same time, Hive's SQL gives users multiple places to integrate their own functionality to do custom analysis, such as User Defined Functions (UDFs).
Hive is not designed for online transaction processing.
Hadoop provides massive scale out and fault tolerance capabilities for data storage and processing on commodity hardware.
Hive is designed to enable easy data summarization, ad-hoc querying and analysis of large volumes of data.
This type hierarchy defines how the types are implicitly converted in the query language.
Hive is a data warehousing infrastructure based on Apache Hadoop.
For details on setting up Hive, Hive Server2, and Beeline, please refer to the Getting Started guide.
So when a query expression expects type1 and the data is of type2, type2 is implicitly converted to type1 if type1 is an ancestor of type2 in the type hierarchy.It provides SQL which enables users to do ad-hoc querying, summarization and data analysis easily.