Difference between SQL and HiveQL

1. Structured Query Language (SQL) :
SQL is a domain-specific language used in programming and designed for managing data held in a relational database management system also known as RDBMS. It is also useful in handling structured data, i.e., data incorporating relations among entities and variables. SQL is a standard language for storing, manipulating and retrieving data in databases.

2. Hive Query Language (HiveQL) :
HiveQL is a query language for Hive to analyze and process structured data in a Meta-store. It is very much similar to SQL and highly scalable. It reuses familiar concepts from the relational database world, such as tables, rows, columns and schema, to ease learning. Hive supports four file formats those are TEXT FILE, SEQUENCE FILE, ORC and RC FILE (Record Columnar File).

Difference between SQL and HiveQL :

On the basis of  SQL HiveQL
Update-commands in table structure UPDATE, DELETE


Manages Relational data Data Structures
Transaction Supported Limited Support Supported
Indexes Supported Supported
Data Types It contain a total of five data types i.e., Integral, floating-point, fixed-point, text and binary strings, temporal It contains a total of 9 data types i.e., Boolean, integral, floating-point, fixed-point, text and binary strings, temporal, array, map, struct.
Functions Hundreds of built-in functions Hundreds of built-in functions
Mapreduce Not Supported Supported
Multitable inserts in table Not supported Supported
Create tabl…as Select Not supported Supported
Select command Supported Supported with SORT BY clause for partial ordering and LIMIT to restrict number of rows returned
Joins Supported Inner joins, outer joins, semi join, map joins, cross joins
Subqueries Supported Only Used in FROM, WHERE, or HAVING clauses
Views Can be Updated Read-only i.e. cannot be updated

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