In yesterday’s blog post we explored the basic architecture of Big Data . In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – NoSQL.

What is NoSQL?

NoSQL stands for Not Relational SQL or Not Only SQL. Lots of people think that NoSQL means there is No SQL, which is not true – they both sound same but the meaning is totally different. NoSQL does use SQL but it uses more than SQL to achieve its goal. As per Wikipedia’s NoSQL Database Definition – “A NoSQL database provides a mechanism for storage and retrieval of data that uses looser consistency models than traditional relational databases.“

Why use NoSQL?

A traditional relation database usually deals with predictable structured data. Whereas as the world has moved forward with unstructured data we often see the limitations of the traditional relational database in dealing with them. For example, nowadays we have data in format of SMS, wave files, photos and video format. It is a bit difficult to manage them by using a traditional relational database. I often see people using BLOB filed to store such a data. BLOB can store the data but when we have to retrieve them or even process them the same BLOB is extremely slow in processing the unstructured data. A NoSQL database is the type of database that can handle unstructured, unorganized and unpredictable data that our business needs it.

Along with the support to unstructured data, the other advantage of NoSQL Database is high performance and high availability.

Eventual Consistency

Additionally to note that NoSQL Database may not provided 100% ACID (Atomicity, Consistency, Isolation, Durability) compliance.  Though, NoSQL Database does not support ACID they provide eventual consistency. That means over the long period of time all updates can be expected to propagate eventually through the system and data will be consistent.

Taxonomy

Taxonomy is the practice of classification of things or concepts and the principles. The NoSQL taxonomy supports column store, document store, key-value stores, and graph databases. We will discuss the taxonomy in detail in later blog posts. Here are few of the examples of the each of the No SQL Category.

• Column: Hbase, Cassandra, Accumulo
• Document: MongoDB, Couchbase, Raven
• Key-value : Dynamo, Riak, Azure, Redis, Cache, GT.m
• Graph: Neo4J, Allegro, Virtuoso, Bigdata

As of now there are over 150 NoSQL Database and you can read everything about them in this single link.

Tomorrow

In tomorrow’s blog post we will discuss Buzz Word – Hadoop.

Reference: Pinal Dave (http://blog.sqlauthority.com)