6 mins Apr 08, 2022 Somendra Yadav WEB Views : 1705
Are you confused while choosing the modern database? Or don't know whether SQL or NoSQL; which one to choose? SQL refers to a decades-old database but is still ubiquitous and effectively being used by Analysts, Engineers, data scientists, and IT decision-makers. However, the increasing volumes of unstructured data, process chunks of data, and the need for storage availability spark interest in different technologies such as NoSQL. 

The big giants like Microsoft, Dell, Accenture, and Cognizant use SQL databases, while on the other hand, companies like Amazon, Adobe, Google, and Netflix use NoSQL. Now, you might be curious to understand the key differences between SQL and NoSQL. First, let's dive into the software world of understanding SQL and NoSQL from the absolute beginning. 

What Is Structured Query Language (SQL)?

SQL is a programming language that differs from a general-purpose programming language such as Python, Java, and JavaScript. It has a specific purpose: to access and manage data in relational databases. It uses relations (referred to as tables) with a schema to manage and store data.  


  1. Oracle  

  2. Microsoft SQL server 

  3. Ingres 

  4. Microsoft office Access 

  5. IBM DB2 

  6. Sybase 

  7. Google Cloud SQL 

  8. Amazon RDS 

  9. PostgreSQL 

What Is Non-SQL Or Not Only SQL (NOSQL)?

It is a non-tabular and non-relational database with specific data models such as document, key-value, and graph formats to create modern applications. It is used for distributed data that requires a large stack of storage needs and can effectively store structured, unstructured, semi-structured, and polymorphic data. 


  1. MongoDB 
  2. Couchbase 
  3. Amazon's Dynamo DB 
  4. CloudDB 
  5. Apache's CouchDB 
  6. MarkLogic 
  7. Oracle NoSQL 
  8. HBase 
  9. Apache's Cassandra DB 
  10. Redis 


Comparison  SQL  NoSQL 
Key Purpose 

It can be used for data 

  1. Storage 
  2. Deletion 
  3. Updation 
  4. Insertion 
  5. Retrieval of data 

It can be used for the maintenance and retrieval of different types of data 

  1. Structured 
  2. Unstructured 
  3. Semi-structured 
  4. Polymorphic 
Schema  Rigid Schema (structured data)  Flexible Schema (unstructured data) 
Data Structure  SQL Data structures 
NoSQL Data structures 
  1. Document-based 
  2. Key-value 
  3. Graph-based 
  4. Wide Column 
Scalability Vertically scaled( add big servers)  Horizontally scaled(add more servers) 
Ideal use cases  It is well-suited for 
  1. Complex queries 
  2. Multi-row transactions 
  3. Dynamic queries 
  4. Legacy systems that built around the relational structure 
It is well suited for 
  1. Unstructured data or document 
  2. Real-time data 
  3. Cloud computing 
  4. Agile business 
  5. Non-complex queries 
Scalable queries due to changing environments 
Hardware  Require powerful hardware to foster vertical scaling  Requires commodity hardware to foster horizontal scaling 
Database transactions  Follow ACID (atomicity, consistency, isolation, and durability) properties  Follow BASE (basic availability, soft-state, and eventual consistency) 
Architectural Relational Non-relational 
Key Features  Features of SQL 
  1. Cross-platform support 
  2. Multi-level Security 
  3. Free 
Features of NoSQL 
  1. High performance 
  2. Scalability 
  3. Flexibility 
Normalization & Joins  Normalization & joins are required  Denormalization & joins are not required 

After the astounding comparisons, let’s come to the SQL vs NoSQL pros and cons. 


When looking for a data management system for your enterprises, you should consider the SQL vs NoSQL scalability, performance, schema, architecture, database transactions, and more. 
Here is the SQL vs NoSQL pros and cons


1. Simplicity 

The SQL databases have a simple structure that can be efficiently managed with simple SQL queries and doesn't require challenging architectural efforts.  

2. Data security 

Don't you think it is great to get high data security? Yes, it is possible with the SQL database because it stores the data in the form of tables which has restricted permission to confidential information.  

3. Lowered data storage footprint 

The lower data storage footprint is due to the optimization and normalization opportunities, resulting in enhanced database performance.  


1. Performance issues 

When a large amount of data in a database and multiple users are logged in simultaneously, it might decrease the query response time.  

2. Limited horizontal scalability 

The SQL database can only be skilled vertically; hence it isn't easy to scale horizontally, slowing down the distributed database performance. 

3. Cost factor 

SQL database can include a high cost for its maintenance and development. In addition, it requires a team of experts to maintain it, which also inhibits an additional cost. 


1.High performance 

NoSQL is generally built to deliver a high performance than SQL. Hence, some NoSQL databases provide impressive data processing speed. 

2. Scalability 

Did you know NoSQL databases are designed to handle large data sets? Therefore, they can be horizontally scaled to lodge more data requiring less maintaining low costs.  

3. Flexibility 

Thanks to the non-rigid structure of the NoSQL database, that can combine and store any type of data.  


1. Data analysis challenges 

Most business and data scientists traditionally choose SQL due to its great data analysis potential, while with a NoSQL database, even the simplest queries need a certain level of expertise.  

2. Lack of support 

It doesn't have a vast community compared to SQL because it was introduced a few years ago. Therefore, it is unable to provide strong support, and it becomes difficult to resolve undocumented issues. 

3. Issues with consistency 

It shows consistency issues while handling a large amount of data and doesn't comprise with data redundancy mechanism. Hence, at the places where consistency issues can be acceptable, like shopping carts being updated and social media posts being alive, NoSQL can be used. Moreover, NoSQL is good in offering exceptional speed and availability rather than consistency.

                             Also Read: Monolithic vs Microservices Architecture

Who is the Real Winner-SQL or NoSQL?

What do you think is the real winner, SQL or NoSQL? Most people think that NoSQL is the clear-cut leader, but that's not certainly true. Many myths and misconceptions are running around, but both have their own advantages, and you need to decide after considering the SQL Vs NoSQL pros and cons and make a smart decision that fits your business needs.  

When SQL and No SQL can be Used?

SQL and NoSQL can be used based on the business needs and requirements-  
1. For a massively distributed system, consider using the Scylla, a distributed NoSQL wide-column store. 
2. If the goal is a vertically scaled database, the go-to option will be an SQL database. 
3. If the input data is relatively challenging to encapsulate and is heterogeneous, NoSQL is the best option. 
4. Is ACID compliance your priority? Look no further than SQL databases. 
5. If the temporary data needs to be stored like session data, wish lists, and shopping carts, you can choose NoSQL. 
6. Do you wish to analyze behavioral-related and customized sessions? Prefer SQL database.

Final Thought: SQL VS NOSQL

The databases SQL and NoSQL have their own importance, and it profoundly depends on your business requirement and objectives. One of the biggest factors in understanding which database is the better choice depends on the type of data that needs to be stored. If you are still confused about which database to use.  

Here is the heck:  

SQL database is the preferred option if you are handling structured data that doesn't change much over time. 
You can consider a NoSQL database if you handle a large chunk of data with little structure. If you are searching for the best software development company in USA that provides an efficient and streamlined database management solution for your enterprise, check out here.