Either to say the term “NoSQL” stands for “non-SQL” or it stands for “not only SQL.”, we do agree (in either case) that NoSQL Databases are Databases that store data in a format other than Relational Tables. NoSQL technologies allow storage and query of unstructured and semi-structured data. NoSQL is used for Big Data and Real-Time Web Apps. For example, companies like LinkedIn, Google, Facebook and Twitter collect terabytes of users’ data every single day.
Several NoSQL databases are now available with designs that address specific limitations in this acquisition process. Scalable distributed databases automatically provide sharding capabilities (the ability to scale across servers natively) for parallel query execution. Of course, as with any other database, structural definition and mapping to unstructured data sets remain largely manual processes.
There are three main reasons, Why NoSQL Databases are rapidly becoming more and more popular:
- The pace of development with NoSQL databases can be much faster than with a SQL database.
- The structure of many different forms of data is more easily handled and evolved with a NoSQL database.
- New application paradigms can be more easily supported.
Types of NoSQL Databases, include:
- Key-Value Store – Key-Value Database
- Column-Oriented Databases
- Document-Oriented Database – Document-Store
- Graph Databases
Some Popular NoSQL Databases : MongoDB, CouchDB, CouchBase, Cassandra, HBase, Redis, Riak, Neo4J.
For Further Reading:
