There many type of databases.
NoSQL was first used in 1998 by Carlo Strozzi while naming his lightweight, open-source “relational” database that did not use SQL. The name came up again in 2009 when Eric Evans and Johan Oskarsson used it to describe non-relational databases. Relational databases are often referred to as SQL systems. The term NoSQL can mean either “No SQL systems” or the more commonly accepted translation of “Not only SQL,” to emphasize the fact some systems might support SQL-like query languages.
Amazon -- DynamoDB
Google -- Firebase
Microsoft uses -- Azure Cosmos
Netflix -- SimpleDB, HBase and Cassandra
NoSQL developed at least in the beginning as a response to web data, the need for processing unstructured data, and the need for faster processing. The NoSQL model uses a distributed database system, meaning a system with multiple computers. The non-relational system is quicker, uses an ad-hoc approach for organizing data, and processes large amounts of differing kinds of data. For general research, NoSQL databases are the better choice for large, unstructured data sets compared with relational databases due to their speed and flexibility.
Not only can NoSQL systems handle both structured and unstructured data, but they can also process unstructured Big Data quickly. This led to organizations such as Facebook, Twitter, LinkedIn, and Google adopting NoSQL systems. These organizations process tremendous amounts of unstructured data, coordinating it to find patterns and gain business insights. Big Data became an official term in 2005.