Where SQL Databases Fail, NoSQL Databases Deliver
NoSQL databases can really help where SQL databases falter. Learn what SQL isn't great for, and why NoSQL is so excellent.
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NoSQL possesses wide variety of different database technologies and these various databases were developed in response to the rise in the volume of data. The types of data stored are users, objects and products. This combined with the frequency in which this data is accessed, the performance and processing needs demanded, result in a much more complicated situation of handling data. Earlier the relational databases were not designed to cope with the scale and agility challenges which today’s modern applications face.
NoSQL did come up with a bold statement. But first, let’s go in more detail and see why SQL databases are challenging:
A - What is SQL Not Good For?
Impedance Mismatch: SQL queries are not very well suited for the object oriented data structures which are used in most applications now.
Storage and Retrieval: Another problem with SQL queries is the storage and retrieval of object with all relational data.
Object-relational Mapping frameworks: Some of these problems are associated with ORM frameworks but still a lot of development effort is required to work around most of the performance and complexity issues.
Exponentially Increased Data: Another set of problems which these relational databases struggle with, is the superfluous amount of data, hence the direct problem ends creating lot of big data problem.
B - Why NoSQL:
NoSQL uses various data models and the main advantage of using varied data models is that they are very good at what they are capable of. It is always suggested to allow these data models do what they are meant for and not to force them for something for which they are not designed for. Let’s see some data types in NoSQL:
B - 1: Types of NoSQL Databases
There are four general types of NoSQL databases having their own specifications:
Key-Value store: Examples - Azure Table storage, Cassandra, Riak, BerkeleyD, DyanmoDB.
Column store which is also known as wide-column stores: Examples include - BigTable, HBase and HyperTable.
Document database: Examples include: MongoDB and CouchDB.
Graph database: Examples include: Neo4J and Polyglot.
C - Benefits of NoSQL:
Adopting NoSQL database environment over relational database has much to do with market drivers and technical requirements.
1. Big data
The volume of data has increased massively. Also O’Reilly termed large voluminous data as “industrial revolution of data”. Big Data is one of the key force which drives growth and popularity of NoSQL for business. The volumes of big data which NoSQL systems such as Hadoop handles exceeds what biggest RDBMS could have handled.
NoSQL databases supports auto-sharding which means that these databases spread data automatically across numbers of servers randomly. This happens without even requiring the application to even be aware of composition of server pool. Data and query load gets automatically balanced across servers. Cloud Computing makes this easier. Developers do not have to construct complex and expensive platforms to support their applications and hence can concentrate on writing their application code.
3. Automatic Replication
Most of the NoSQL databases also support automatic replication. Hence, developers get high availability and disaster recovery options without even involving distinct applications to manage such tasks.
NoSQL Implementation in Organization:
Conclusively, NoSQL databases are becoming a very important part of the database landscape therefore when used suitably it can yield real benefits. Organization begins with small-scale trial of a NoSQL database in their organization which makes it quite easier for them to develop an understanding of technology at low stakes. Also, NoSQL databases are open-source which means that they can be downloaded and hence can be implemented without the worry of expenses. But, it is very necessary to choose the right NoSQL database for your application.
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