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March 14, 2024
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 min read

NoSQL 101 : What You Need To Know

NoSQL 101 : What You Need To Know

NoSQL database management system is a unique type of DBMS aimed at addressing and managing a large amount of unstructured or semi-structured data. While conventional relational databases store information in tables using fixed schemas, NoSQL databases employ flexible data models that can adapt to evolving data structures and can be horizontally scaled for handling more information. The term NoSQL was initially known as “non-SQL” or “non-relational” databases, but now it refers to “not only SQL” because NoSQL databases have added many various database architectures and data models to their spectrum. In today’s article, we will try to explain NoSQL briefly.

TL;DR

Let's buckle up! 

NoSQL databases are the most suitable option for processing uncertain, unrelated, or rapidly changing data. Its flexible structure, which does not require a database schema, makes it intuitive for developers to use, making it easier to adapt to rapidly changing data requirements.


A Brief History Of NoSQL

In the 2000s, NoSQL databases came into being because the cost of storage had decreased significantly. It became unnecessary to create a highly complex and difficult model to avoid data redundancy, all thanks to NoSQL databases that addressed this issue. The software industry was shifting from storage costs to developer costs as the primary expense of software development, and so NoSQL databases were built to enhance developer productivity.

The reduction in storage prices has been so swift and sharp that applications have had to deal with more data than they can handle, both for storage and querying purposes. The data type can be structured or semi-structured; there are also databases with polymorphic data. And it’s quite hard to specify a schema before working with the data. NoSQL enables developers to save numerous elements of unstructured facts and that presents them with far-reaching control and freedom.

At the same time, the Agile Manifesto has become a popular alternative, and coders have started questioning how to develop software differently. They were realizing the need to be able to switch gears on the fly with new requirements. They wanted to be able to change any part of their system very quickly—starting from user interface design and ending at the database level. A NoSQL database allowed them to have this kind of flexibility.

To add, in the sphere of technology and infrastructure, cloud computing has gained popularity as a means to store and host applications and data in public clouds. Organizations are interested in the ability to replicate their data on multiple servers located in different regions so that even if some servers fail, their applications will continue working. They aim not to grow vertically, but horizontally by distributing the application load across multiple servers. Finally, they desire to have an intelligent system that can automatically select the best server for placing user data based on its location. All of these features are present in certain NoSQL databases such as MongoDB.

Usage Of NoSQL Databases

In the area of document databases, these systems arrange data in unstructured documents with JSON or XML format. The queries are done by using document-oriented query languages, which allow for versatile data access and manipulation.

One of the types of databases is key-value stores. This category is designed to store information as a simple value paired with a unique key and to optimize this structure for fast read and write operations. Key-value stores are well-suited for situations that need high-performance data access and retrieval.

Information in a column-family store is organized into column families, which are sets of columns taken as one unit. The great thing about these databases is that they are built for effective searching of extensive data collections, so they would be a smart solution for any data-heavy system or application.

Graph databases are types of database management systems where data is structured into interconnected nodes and edges, making it easier to portray and explore the intricacies of relationships between data entities. They can be effectively employed in network analysis, social networking modeling, and recommendation systems applications.

NoSQL databases are widespread in many industries, especially where data is voluminous and high in velocity, requiring immediate processing as well as analysis. The social media analytics industry, e-commerce industry, and gaming industry are some of the areas that make use of NoSQL databases for extracting insights and making informed decisions. Furthermore, these databases can be found within content management systems, document management systems, and customer relationship management systems.

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