Gain competitive advantage with NoSQL databases

Gain competitive advantage with NoSQL databases

Gain competitive advantage with NoSQL databases

Relational databases have ruled the technology world for a long time. However with the massive transformation of industries into a data-driven entities the need for agile and  responsive technologies has grown to fast-track the organizations. This shift has caused enormous amounts of unstructured data to emanate from diverse sources which relational databases failed to manage and store. That is when NoSQL databases came into the picture.

 As the name implies NoSQL, also called as Not-only-SQL are the databases that let the developers store/manage unstructured data and perform complex analytical operations on it as well. A wide range of NoSQL databases are suitable for varied use cases hence the companies need not be confined to single database platform anymore.

As per a report by AlliedMarketResearch, Global market for NoSQL, is slated to grow, due to adoption of a wide variety of applications, such as web session management, mobile app development and e-commerce, during the forecast period of 2014-2020.

Read Also:
How Data Can Help Farmers Protect the Earth

 Want to know what is MongoDB? Read this extensive tutorial!

Relational databases emerged in late 20th century when there was no sign of internet, mobile computing, cloud, and other technologies that have become an inseparable part of today’s economy. These databases used to run on big servers and strictly suitable for use-cases when the data was purely structured. However with the advent of digitization relational databases started lacking to keep up with changing requirements of the fast-paced technology world.

IDC says that approximately 90% of all data produced this decade would be unorganized and unstructured.

The reason behind this failure was the constraints associated with the relational databases. Some of the reasons that took relational databases to lag behind were:

NoSQL databases resolve these issues as these have a dynamic structure which allows the systems to be responsive and agile.

Till yet we learned the reasons that worked as a catalyst for the failure of relational databases.

Read Also:
How Any Business Can Develop a Big Data Mindset


Read Also:
Instrumenting your data for real-time analysis and streaming
Read Also:
Data Warehouses and In-Memory Technologies: Myths and Reality
Read Also:
In five years, SaaS will be the cloud that matters
Read Also:
5 Developments in Data Analytics to Watch in 2017 

Leave a Reply

Your email address will not be published. Required fields are marked *