Need for Big Data Analytics Drives Demand for NoSQL Databases

NoSQL is a type of database used to store and retrieve data that can’t or isn’t fit to be classified into relational databases. The latter database type almost exclusively uses structured query language (SQL) for the storage of data. As a result, the term ‘NoSQL’ is most commonly interpreted as ‘Not only SQL’, indicating that it can accommodate non-SQL data storage languages as well.

Relational databases store data in tabular format, necessarily presenting each datum in a one-to-one relationship thanks to the position of each cell as the unique intersection of its row and column. This limits the database as only one format of data can be presented. NoSQL databases get over this problem through their simpler design, horizontal scalability, and detailed customization that can be configured regarding the availability of the database.

NoSQL databases have exploded onto the global database management scenario thanks to the rapid emergence of big data analytics. The NoSQL market is reliant on the growth of the big data analytics market to a large degree.

  • Increasing Complexity of Data: Due to the proliferation of social media and other such complex tools, the need is mounting for data analytic programs that can manage various types of data, probably containing one-to-many or many-to-many relationships, something that relational databases can’t handle. NoSQL databases help big data analytics store and manage complex data, increasing their usage in big data analytics software.
  • Need for Data Storage in Big Data Analytics: Among the various components of big data analytics services, storage is expected to show the fastest growth in the coming years, growing at a CAGR of more than 40% from 2012 to 2018. The issue of storage will become even starker, as the influx of data in today’s highly digital world is increasing in a compound manner, with each new packet of data adding to the previous total and giving rise to new avenues of data generation. This has given the NoSQL market a great opportunity in the big data analytics field in the coming years.

 On the other hand, the NoSQL market faces two formidable challenges.

Lack of Skilled Personnel: Due to intensive and unique nature of NoSQL databases, their operation requires highly skilled and trained personnel. The lack of the same is a major restraint for the market to overcome in the coming years, and the cyclical nature of the issue means that it can only be solved by further expansion of the market with the help of potentially risky investment from data storage giants.

  • Firm Presence of SQL: To further complicate matters, the infrastructural support for SQL databases is already strong in the tech world. Like any new entrant in the technological arena, NoSQL will first need to overcome the hurdles set up by the establishment of SQL as the language of choice, before expanding its own scope considerably.

In spite of these challenges, the positives offered by NoSQL databases are expected to propel the market at a stunning CAGR of more than 53% from 2013 to 2018.