No Sql - Introduction

NO SQL stands for ‘NOT ONLY SQL’.No SQL is a different dimension in database which is different than traditional database system and used to hold a large dataset.This kind of database can include a wide variety of database like key,value pair,document,columnar and graph formats .The idea of NO SQL database comes up when we start facing the issue with traditional database system.Both the system and has some advantages and disadvantages .

The difference between SQL and NO SQL can be done on various categories but one of the primary category for the differentiation is on schema.

The traditional database is more of predefined schema based database while No Sql is free from any schema or we can say that No Sql is a schema less database.

NoSQL databases are built to allow the insertion of data without a predefined schema. That makes it easy to make significant application changes in real-time, without worrying about service interruptions – which means development is faster, code integration is more reliable, and less database administrator time is needed.

Different kind of No Sql database :-

Key-value stores are the simplest NoSQL databases. Every single item in the database is stored as an attribute name, or key, together with its value. Examples of key-value stores are Riak and Voldemort. Some key-value stores, such as Redis, allow each value to have a type, such as "integer", which adds functionality.

Document databases pair each key with a complex data structure known as a document. Documents can contain many different key-value pairs, or key-array pairs, or even nested documents.

Wide-column stores such as Cassandra and HBase are optimized for queries over large datasets, and store columns of data together, instead of rows.

Graph stores are used to store information about networks, such as social connections. Graph stores include Neo4J and HyperGraphDB.

Where can we use No SQL databases ?

The No Sql databases are very helpful us in many ways but we need to figure out where we can use the No Sql database .

• The main priority is speed and we can compromise on the consistency of the data.
• When we have a large dataset and changing the schema can be a cumbersome job.
• If we are having some unstructured data and it is one of the toughest job is to handle them in traditional relational database.

Limitation with No Sql :

• There is nothing called “free lunch “.The No Sql database comes up with some limitation.Such kind of databases are not useful where we need a lot of consistency and reliability in data .such kind of safeguards are not allowed in No Sql database .
• Such kind of system are new and still need some time to bring confidence at the user level.