According to Domo, a platform that has been highlighting data in terms of its volume, velocity and variety since 2013, has seen a steep rise in the percentage of internet population and the data being generated every single minute! In its 7th consecutive report, the internet has reached 56.1% of the total world’s population and now represents 4.3 billion people, this is a 9% increase from January 2018. And as far as the trend goes, there won’t be a negative curve in the graph for a long time. This increase can be attributed to increased access to social media, popular internet services like YouTube, Netflix, etc. and interconnected sensors – the building blocks of the Internet of Things.
Given this staggering increase of data, managing it can be quite a task and relational databases are not quite adept at processing this rapidly. This is due to the fact that the new data coming in does not always fit into the tight schema followed by a relational database. NoSQL database, on the other hand, can easily manage huge volumes of data and the operations performed over it.
For instance, if you have a website that is popular and say has at least 10,000 registered customers, and growing daily, each of these customers will follow their own life-cycle and processes. On the front end, they would be loading pages, similar items, adding products to cart etc. but on the backend, whenever an operation is performed, the data is retrieved from the database, the similar items are suggested taking into account the number of times a particular type of query was run, and so on and so forth.
If all these operations take time to run say maybe more than a few seconds or a minute (i.e retrieving/reading from the database, searching, finding and displaying) the user might abandon the cart and go somewhere else.
The reason for slow operations could either be slow website loading speed or a slow backend that processes your data. If you have a relational database, chances are there would be innumerable rows and columns, and finding the right match would take a long time. On the other hand, if you use a NoSQL database, this problem would be significantly less.
So is this a real-time example? It is, Amazon uses DynamoDB as mentioned initially, and Google uses BigTable, both an example of a NoSQL database.
To put it simply, here are the 4 reasons to switch to a NoSQL database:
1.Highly scalable
2.Able to handle large volumes of data – structures, and semi-structured
3.Schema-less
4.Quick iterations
