SQL databases are mainly called relational databases (SGBDR); whereas NoSQL database is mainly referred to as distributed or non-relational database.
SQL databases are table-based databases while NoSQL databases are databases based on key-value pairs, graphical databases, etc. This means that SQL databases represent data in the form of tables made up of n number of rows of data, whereas NoSQL databases are the collection of key-value pairs, documents, graphical databases, etc. that do not have standard schema definitions.
SQL databases have a predefined schema while NoSQL databases have a dynamic schema for unstructured data.
SQL databases are scalable vertically, while NoSQL databases are scalable horizontally. SQL databases are scaled by increasing the power of the hardware. NoSQL databases are scaled by increasing the number of database servers in the resource pool to reduce the load.
SQL databases use SQL (structured query language) to define and manipulate data, which is very powerful. In NoSQL database, queries are focused on document collection. Sometimes it is also called UnQL (Unstructured Query Language). The syntax for using UnQL varies from base to base.
Examples of SQL databases: MySql, Oracle, Sqlite, Postgres and MS-SQL. Examples of NoSQL databases: MongoDB, BigTable, Redis, RavenDb, Cassandra, Hbase, Neo4j and CouchDb For complex queries: SQL databases are ideal for the environment requiring many queries, while NoSQL databases are not suitable for complex queries.
At a high level, NoSQL does not have standard interfaces for performing complex queries, and the queries themselves in NoSQL are not as powerful as the SQL query language. For the type of data to store: SQL databases are not suitable for hierarchical data storage. However, NoSQL database is better suited for hierarchical data storage because it follows the key-value pair method to store data similar to JSON data. NoSQL databases are highly preferred for large data sets (i.e. for large data). Hbase is an example for this.
Scalability: In most situations, SQL databases are vertically scalable. You can handle the increased load by increasing CPU, RAM, SSD, etc. on a single server. On the other hand, NoSQL databases are horizontally scalable. You can just add a few more servers easily into your NoSQL database infrastructure to handle the heavy traffic.
For Highly Transactional Applications: SQL databases are best suited for heavy-duty transactional applications because they are more stable and promise atomicity as well as data integrity. While you can use NoSQL for transactional purposes, it is still not comparable and can be used sufficiently for complex transactional applications.
For properties: SQL databases focus on ACID (Atomicity, Consistency, Isolation, and Durability) properties, while NoSQL database follows the Brewers CAP (Consistency, Availability, and Partition Tolerance) theorem.
Why should you use SQL database?
SQL actively protects the integrity of your database by providing ACID compliance. Because of its structured data, you don’t need any built-in system support to work with different types of data. Additionally, SQL is the most recommended option by many companies due to its predefined structure and schemas.
Why should you use the NoSQL database?
It is growing in popularity by allowing you to store different types of data together and you can easily scale by spreading out multiple servers. If you need to develop an application within a certain time frame, you can opt for NoSQL, which will speed up your performance thanks to its rapid development phase.
Each company will have their own preferences depending on the requirements of the project. So determine your needs and the database that judiciously provides the integrated support for the development of your project.