What are the differences between SQL and HiveQL?
SQL and HiveQL are programming language that helps to improve the design of the database. Some people tend to use them alternating but they are quite different.
The lesson provides the core differences between SQL and HiveQl in tabular form for easy understanding. Let’s find out:
What Is SQL?
SQL is an abbreviation of Structured Query Language and it is a language that is quite vital for working with the database.
The database does not understand any language and this is the reason why we use SQL to make work much easier.
This declarative language deals with structured data that is meant for relational database management. It normally supports schema for data storage.
SQL is ideal for database systems since you can frequently make some modifications to it. Besides that, SQL is mainly used for better performance.
What Is HiveQL?
HiveQL is using a combination of SQL-92, Oracle’s SQL language, and MySQL. It has some improved features of SQL versions like analytics function from SQL 2003.
Some common extensions of HiveQL are multiple inserts, TRANSFORM, MAP, and REDUCE.
Comparison Chart: SQL vs HiveQL
|Subqueries||Used in any clause||Used in FROM, WHERE, or HAVING clauses|
|Transactions||Supported||Limited support supported|
|Updates||Update, Delete Insert||No Update, Delete Insert|
|Data Types||Integral, floating-point, fixed-point, text and binary strings, temporal||Boolean, integral, floating-point, fixed-point, text and binary strings, temporal, array, map, struct|
|Functions||Hundreds of built-in functions||A limited number of built-in functions|
|Operation for||Structured data and is for RDBMS||Structured data|
|Schema||Data storage||Data insertion|
|Usage||When we need frequent modification in records.||To query large data sets and analyze historical data|
|Performance||Better performance||Best performance|
Core Differences between SQL and HiveQL In Point Form
- SQL is for structured data and is for RDBMS while HiveQL is for structured data only.
- HiveQL support schema for data insertion while SQL support schema for data storage
- SQL is used when we need frequent modification in records whereas HiveQL to query large data sets and analyze historical data.
- SQL has hundreds of built-in functions while HiveQL has a limited number of built-in functions.
- SQL support updates, delete, and insert while HiveQL does not support any.
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Summary of SQL Vs HiveQL
Both of these two programming languages are declarative language and they are frequently used in the database.
The core difference between SQL and HiveQL is that Hive language is an advanced version of SQL.
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