What is necessary for top-tier Web sites, according to proponents of NoSQL, is massive scalability, low latency, the ability to grow the capacity of your database on demand and an easier programming model. These, and others, are things which, according to them, SQL RDBMSes just don't provide in a cost-effective manner.
NoSQL database systems are developed to manage large volumes of data that do not necessarily follow a fixed schema. Data is partitioned among different machines (for performance reasons and size limitations) so JOIN operations are not usable.Documents are addressed in the database via a unique key that represents that document.No SQl Suuports CAP Property (Consistency, Availability, Partition tolerance)
C - Consistency
A - Availability
P - Partition tolerance
Partial partition tolerance for these databases is obtained by mirroring database clusters between multiple data centers. The advantage these databases have over a traditional RDBMS is that with the work spread over all of those machines, you can achieve ultra-low latency even when there are extremely high numbers of reads and writes, and with all those machines, you can analyze massive amounts of data quickly.This is meaningless when the database is on a single server
NoSQL implementations can be categorized by their manner of implementation:
1) Document store
Compared to relational databases, for example, collections could be considered as tables as well as documents could be considered as records.But they are different: every record in a table has the same sequence of fields, while documents in a collection could have fields that are completely different.Documents are addressed in the database via a unique key that represents that document. One of the other defining characteristics of a document-oriented database is that, beyond the simple key-document (or key-value) lookup that you can use to retrieve a document, the database will offer an API or query language that will allow you to retrieve documents based on their contents.
Having keys and values are the so-called document databases. A document, in this case, is a collection of various fields of information. Each individual document can have a different number of fields of varying lengths. These databases are useful if you have a lot of semi-structured data, and they are a good fit for object-oriented programming models
Eg :CouchDB, MongoDB
This kind of database is designed for data whose relations are well represented as a graph (elements interconnected with an undetermined number of relations between them). The kind of data could be social relations, public transport links, road maps or network topologies
Eg: Neo4j, InfoGrid and HyperGraphDB
3) Key-value store
Key-value stores allow the application to store its data in a schema-less way. The data could be stored in a datatype of a programming language or an object.Each piece of data that goes into the database is given a key, and when you want the data back, you use the key to get
4) XML databases
It does not use SQL as its query language.
It may not give full ACID guarantees.
It has a distributed, fault-tolerant architecture
5) Wide-column databases
It tend to draw inspiration from Google's BigTable model.
Eg: Cassandra, HBase
Advantages of NoSQL
Storage Type: Column Based NoSQL Databases, Document Based NoSQL Databases, Graph Based NoSQL Databases, Key-Value Based NoSQL Databases
License Type: AGPL NoSQL Databases, Apache NoSQL Databases, BSD NoSQL Databases, GPL NoSQL Databases, Open Source NoSQL Databases, Proprietary NoSQL Databases
Implementation Language: C NoSQL Databases, C++ NoSQL Databases, Erlang NoSQL Databases, Java NoSQL Databases, Python NoSQL Databases
Data Storage: BDB NoSQL Databases, Disk NoSQL Databases, GFS NoSQL Databases, Hadoop NoSQL Databases, Plug-in NoSQL Databases, RAM NoSQL Databases, S3 NoSQL Databases