SQL vs No SQL: The Difference and The Decision

Sep 27, 2019

Prakunj Chaudhary
Software Developer

If you take into account what experts are claiming the world's data is growing at an unprecedented rate. This accumulation of big data has lead to a change of structuring of storage and management of said data. Flaws have started appearing in the revered traditional methods of storage and attention is now being focused on trying to update this conundrum.

Earlier all data used to be archived in the form of physical files filling up rooms and rooms of a large corporation and then came in computers. The data increased but the storage spaces could now be a lot more compact.

Somewhere in the 1970s, SQL databases were introduced and integrated into the basic structure of the infrastructure of organizations. Along the same lines, the world's most popular database is MySQL and powers large scale websites like Google and Facebook. It is an open-source database and that has also been a large part of its popularity.

But as all things in technology are, there is constant innovation taking place and there is a new buzzword in the market "NoSQL".

What is SQL?

Structured Query Language (SQL) is the defining core of relational databases. A relational database is one that defines relationships in the form of tables. Effective use of the SQL language helps in the optimization and maintenance of databases.

What is NoSQL?

This is a non-relational data management system. It is usually used for storing copious amounts of unrelated data. It works for companies that collect big data and real-time web applications. It is a concept that was introduced in 1998 and is a database system that can store structured, semi-structured and polymorphic data.


The difference between SQL and NoSQL is one of the relational and non-relational databases. Below we will go through each of their features in detail to see what fits where.


SQL uses structured query language for defining and manipulating data. It is considered to be a good choice as it is versatile and widely used but it is also on the other hand highly restrictive. It requires its users to have a predefined schema beyond which any data that does not fit into this predefined schema can be highly disruptive to the whole system.

NoSQL, on the other hand, is highly dynamic and shifts and molds its structure as the data comes in.


SQL data is essentially stored in a table format whereas NoSQL can be anything from a document-based, key-value pair to graph databases. This makes SQL databases a great option for data that has multi-row transactions. NoSQL is ideal in terms of data that comes in large quantities and varying formats.


SQL is vertically scalable I.e. you can increase the load that a single server bears simply by adding things like CPU, RAM or SSD. NoSQL is horizontally scalable. This implies that more traffic can be handled by adding more servers in your database.

Complexity of Queries

SQL is a better fit for complex queries as the schema is better structures and the data is stored in a tabular format making it easier to navigate. Due to the lack of a structured language in NoSQL complex queries are not a good fit.

Data Storage

Data in SQL needs to be relational in nature to be stored effectively but as the data volume increases it becomes very difficult to take multiple rows and columns and relate them to one another. So a NoSQL database here fits a lot better.

Understanding the Base

SQL is formed on that basis of ACID properties which stands for Atomicity, Consistency, Isolation & Durability. NoSQL, on the other hand, flaunts the Brewers Cap theorem which is Consistency, availability and partition tolerance.

External Support

Due to the number of years that SQL has been in existence the support that you receive is tremendous. NoSQL, however, has only a limited number of experts that can help you should a problem arise.

To understand their difference better let's take a look into MySQL and MongoDB


This is one of the world's most used open-source relational database management systems. It works on various platforms and is backed by Oracle. It provides multi-user access to garner support from many storage engines.


This is a non-relational database. MongoDB stores all its data in documents to process faster and sort out the relative information.

Key Areas MySQL MongoDB
Language Used Structured Query Language MongoDB Query Language
Schema Pre-Defined No Restrictions
Relationships Supports JOIN statement Does not support
Security Privilege-security base model Role-based access control
Speed Structured Query Language MongoDB Query Language
Language Used Slower than MongoDB Fast
Support Excellent Excellent
  • Triggers & SSL Support
  • Provides text searching and indexing
  • Query caching
  • Integrated replication support
  • Different storage engines
  • Auto-sharding
  • Comprehensive secondary indexes
  • In-memory speed
  • Native replication
  • Embedded data models support
Fit For Structured Data, Small datasets Unstructured Data, large datasets
Community Large and Vibrant Comparatively Smaller

NoSQL databases are on the rise. Even though they limited advantages, the truth is all data today is being converted to big data. NoSQL might be a newer player in the game but constant improvement is taking place and a lot of big names are migrating towards NoSQL. But just like any other decision in a company, this is also one which needs a long thought.

Prakunj Chaudhary
Software Developer