Relational Databases Vs No-SQL Databases

 

In the modern world, there are two major database types are commonly used by considering the structure of those databases. They are:

1. Relational Databases (SQL Databases)
2. Non Relational Databases (NoSQL Databases)

Further, those Relational and Non Relational databases are also known as SQL Databases and NoSQL databases by considering their Query Language. According to your application requirements, performances, size of the data set and budget of the project you may choose which type of these databases you may use for the particular project. In the next chapters we'll further discuss what are the measurements we have too consider to choose a particular database type and how to choose it properly.

Firstly before dig in to the deep of each database type, let's have a quick look at the definitions of those database types.

Relational Databases (SQL Databases)

Relational databases have stored data in a tabular format (table based data structure) with a strict and required a predefined schema which identifies the structure of the database or the table. Since the nature of storing data in Relational Databases, these databases are vertically scalable and also more expensive with the usage due to the data growing reasons.

Non Relational Databases (NoSQL Databases)

Non Relational Databases could be consist of any of the following types. They are:

1. Key-Value Pairs
2. Wide Column Stores
3. Document Based
4. Graph Databases (Supports Relationships)

The following image will display the statistics of Performance, Scalability, Flexibility and Complexity against each of these Non Relational Database types mentioned above.  

Since, No SQL databases works without any predefined structure (Unstructured), it allows you to work more freely than structured databases. Non Relational databases have a nature of horizontal scaling which provides more cost effective than the Relational Databases when considering data growing scenarios.

History of Relational Databases and Immigration of Non-Relational Databases

Relational databases have been dominated around the globe for about 40 years(approximately). Those databases've worked well for the times when data structures much more simple and static. The traditional SQL-based relational database, on the other hand, was less able to handle quickly expanding data quantities and the increased complexities of data structures as technology and big data applications improved. Non-relational, NoSQL databases have grown in popularity in recent years as a more flexible, scalable, and cost-effective alternative to standard SQL-based relational databases.

Comparison Between Relational Databases & Non Relational Databases

An in detailed comparison between Relational & Non Relational databases has been displayed in the below table by considering the statistics for main features of Performance, Reliability, Availability, Consistency, Data Storage and Scalability.

 

Pros & Cons of using Relational Data Model & Non Relational Data Models

1. Relational Data Model

• Pros:
• Easy to use and setup.
• Universal, compatible with many tools.
• Good at high performance work loads.
• Good at structure data.
• Have a huge community around the globe.
• Standard interface for executing complex queries (Recommended for complex queries since it have JOINS or Join like operations). 
• Best suited for huge load and complex transactional applications.
• Cons:        
• Time consuming to understand and design the structure of the database.
• Could be difficult to scale

      2. Non Relational Data Models

• Pros:
• No investment to design the model
• Rapid development cycles
• Faster than SQL in general usage
• Runs well in cloud 
• Cons
• Unsuited for interconnected data.
• Still not have a huge community than SQL (Technology still maturing).
• Could have slower response time.
• Not good for executing complex queries (Since it not supports JOINS).
• Not suited for huge load and complex transactional applications.