The database is the essence of a business. If you are working in an IT company or any other institute, the database is an essential part. People connected to information technology already know the perks of RDBMS (Relational database management system) and SQL (structured query language). 

The data is sorted and arranged wonderfully, but what happens when the data is unstructured? Unstructured data is a large amount of data that is never organized before and has no data model & schema. 

There must be a way to help us store unorganized data with ease. 

NoSQL Database: 

NoSQL stores the data way differently than SQL. People were looking for ways to deal with data redundancies, duplication, and complex data. There was no way to deal with optimizing data after a certain point. 

The data storage became cheaper day by day, but the applications needed to store data became expensive. That’s when NoSQL came in 2002. NoSQL allowed the developers to store massive data and give flexibility too. It requires no joints, fixed schemas, and is scalable. It has a variety of types depending upon the data model. Deals with structured, non-structure & semi-structured data. 

Example: 

Every kind of data that has no quantity and all type of qualitative data is dealt in NoSQL database. It deals in data collected from different unstructured sources like satellite images, customer behaviors and the activities they perform on PCs and mobile phones.  etc.

So, in short, it can provide a deep knowledge of customer behavior and trends.

• Audio files
• Text files
• Social Media posts
• Mobile user activities

Features:

• In general, a NoSQL database is non-relational and flexible. 
• A NoSQL database helps distribute data stores with massive data storage requirements. 
• NoSQL databases are a good fit for particular data models and flexible schemas that allow for the development of modern applications. 
• It is for Big data & real-time web applications. 
• NoSQL databases are better for requirements that relate to cloud, mobile, social media, and big data. 
• Many NoSQL databases achieve high performance despite having a limited database configuration range.
• Because NoSQL databases are an upgraded form of database systems, they do not necessitate a large team of data managers to perform minor tasks or manage the system.

SQL Database:

 SQL skills are high demand since the start of 1986. Many top-tier companies use RDBMS and require administrators who are fluent in SQL. It is commonly used to perform tasks in a database like an update, delete, insert data, etc. All these common commands are used to achieve most goals in RDBMS. 

Multiple governments and private working sectors use SQL to get their desired data. E-commerce sites also use SQL so that the users can get products with ease. 

Example:

Here is an example of a class schedule. Imagine there are two faculty members in a school (say A & B). A is assigned ID 1 and B is assigned ID 2. There are two classes Y & Z. We can easily store data about when is A taking class Y and when is A taking class Z. We can also retrieve data about their schedule easily.

We can see in table three that 1 is taking class Z and 2 is taking class Y at the given times. The data was already sorted so with little query instructions we got to know who takes class at what time.

TABLE 1:

TABLE 2:

TABLE 3:

Other examples:

• Data gathered from an attendance management system
• Data from a Point of sales software
• Data stored in spreadsheets & tables
• CRM software

 Features:

• Flexible queries, which allow support to a wide range of workloads
• A smaller footprint optimizes database performance and resource usage through standardization and other optimization opportunities.
• Data integrity interpretations that are strong and well-understood, atomicity, consistency, isolation, and durability are database properties that ensure payment information.
• Allows engines to optimize concerns to fit on-disk representations by extracting data over underlying implementations.
• SQL database conceptual frameworks depict relational, tabular data with consistency and integrity constraints.

When to use SQL & NoSQL:

There is no doubt that SQL and NoSQL are among the best in their respective fields. SQL is the most popular programming language for RDBMS, and NoSQL is the software of choice for storing structured, unstructured, and semi-structured data.

SQL: 

SQL, an open-source and free RDBMS, is perhaps the most well-known SQL dialect. It is widely used in web applications and is well known for its compatibility, support, and average performance. It is more acceptable when the data size is small, fundamentally modeled as tabular, and reliability is crucial in systems.

SQL is the best relational database to use when the relationship between data sets is well-defined and highly accessible. It is also the best method for determining data integrity.

NoSQL:

NoSQL manages graph or hierarchical data, large data sets that mutate significantly, and businesses that are flourishing & lack data schemata. With write consistency and eventual consistency effects of grouping on data access & storage must be considered. 

It is user-friendly, and you require fewer resources to manage it. As mentioned earlier, it is a one-stop solution to all database-related problems. SQL is easy to understand, but soon NoSQL will get the better part of the market.