While relational databases are the most widely used application in big data, they are not suited for handling the exponential growth of real-time data. For example, the growth of information on the internet is a challenge for relational databases. Each day the world creates 2.5 quintillion bytes of data, with 90% of the data generated being unstructured. By 2020, it is estimated that over 40 Zettabytes of data will be created.
To help overcome the challenges of this unstructured growth, many developers have been switching to “NoSQL” or “Not Only SQL” databases. NoSQL database systems are distributed, non-relational databases that also use non-SQL language and mechanisms in working with data. NoSQL databases can be found in companies like Amazon, Google, Netflix, and Facebook that are dependent on large volumes of data not suited to relational databases. These databases can work efficiently with current unstructured data like social media, email, and documents. NoSQL has a simple query language with high scalability and reliability.
In the relational database or RDBMS, there are several other limitations besides the handling of unstructured data. For example, the scalability of relational databases includes distribution across multiple servers which can be challenging. There is also a catching layer issue where distributed cache can cause de-normalization. Additionally, there can be sharing problems with rebalancing issues. Not to mention that the cost of dealing with billions of rows in traditional databases can get expensive.
On the other hand, with NoSQL databases, the workload can be automatically spread across multiple servers. Also, unlike RDBMS, NoSQL is highly distributable with clusters of servers which can hold the database. It has cached data in memory which is transparent to application developers and users. And, it allows easy scaling to adapt to the complexity of the cloud. With lots of open-source options, NoSQL technology enables developers to try the software before buying the product. Since a DBA is not needed to refactor SQL and create materialized views, this can also potentially reduce cost.
While NoSQL is an expanding field that challenges many assumptions made by companies around maintaining legacy systems, is a credible movement that is solving real problems posed by big data.