SQL vs NO SQL vs NEW SQL

SQL stands for Structured Query Language. Which is based on relational algebra and schema is fixed in this which means data is stored in the form of columns and tables. SQL follows ACID properties which means Atomicity, Consistency, Isolation, and Durability are maintained. There are three types of languages present in SQL :

• Data Definition Language  
• Data Manipulation Language  
• Data Control Language

Examples: 

Commercial: Oracle, IBM
Open Source: Mysql

NoSql stands for no-SQL which can be related to non-relational. In a NoSQL database storage and retrieval of data done in other than tabular relations are used in relational databases therefore it is schema-free. NoSQL is also an open-source and distributed type of database.
There are four categories depending on the type of data model they support:

• Document Stores                                               
• Graph Database
• Wide Column Databases                                
• Key-value stores

Examples: Cassandra, MongoDB, CouchDB

NewSQL is a modern relational database whose goal is to combine ACID guarantees of SQL with the scalability and high performance of NoSQL. It is made using modern programming languages and technology that wasn’t available before.

Examples: VoltDB, Clustrix

FEATURES	SQL	NO SQL	NEW SQL
Schema	It is schema-fix.	It is schema-free.	It is both schema-fix and schema-free.
Base Properties/Theorem	It strictly follows ACID properties.	It follows the CAP theorem.	It takes care of ACID properties.
Security	It is secure.	It is less secure.	It is moderately secure.
Databases	No distributed database.	Distributed database.	Distributed database.
Query Language	It supports SQL as a query language.	It does not support old SQL but supports UQL.	It supports SQL with improved functions and features.
Scalability	It is vertically scalable.	It is only vertically scalable.	It is both vertically and horizontally scalable.
Types of database	Relational database.	Non-relational database.	Relational database but not purely.
Online processing	Online transaction processing but not full functionality.	Online analytical processing.	Online transaction processing with full functionality.
Query Handling	Simple queries can be handled.	Complex queries can be directed better than SQL.	Highly efficient for complex queries.
Example	MySQL	MongoDB	Cockroach DB.

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