Differences Between Relational And Non-Relational Databases That Every Developer Must Know

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What comes to mind when we talk about a database? A secure place to store files that can be accessed later as per the requirement. Yes, a database is exactly that. Oracle defines a database as “an organized collection of structured information, or data, typically stored electronically in a computer system.” 

Typically, data in database systems are organised into tables, rows, and columns. These databases are also called relational databases. However, the definition of a database slightly changed when No-SQL databases got popular in the 2000s. A No-SQL database is a system for storing and retrieving data that is not represented by tabular relations.

Herein lies the dilemma of selecting a database from among so many alternatives for a project. The answer, of course, is directly proportionate to the type of project you’ll be working on. 

But first, I’ll try to explain in brief about the two databases.

Relational Databases

A relational database, also known as a Relational Database Management System (RDBMS) or SQL database, holds the data in the form of rows and columns that form tables, and tables that are related to one another by ‘keys,’ or information shared by both relations. A row in a table is referred to as a ‘record’ in a relational database, and a table is referred to as a ‘relation.’

It is primarily used for managing structured data in which there is a relationship between various entities and variables of the data.


  • A single standard language is used across all RDBMS.
  • It has a predefined schema that is useful in many use cases.
  • Different responsibilities are defined using a single uniform language (DDL) such as developer, user, DBA, etc.
  • It adheres to the ACID principles (atomicity, consistency, isolation, and durability), ensuring the overall stability, security, and predictability of the database and each transaction.
  • It has an incomparable speed when obtaining database records.


  • It has a complicated procedure for interacting.
  • It is very difficult to scale the database when it grows larger.
  • It is very expensive to handle big data as it needs hardware upgrades for scaling.
  • It has no support for blobs of data such as files or images.

Some examples of Relational databases

  • Oracle
  • Microsoft SQL server
  • PostgreSQL
  • MySQL

Non-relational Database

A non-relational database, also known as a NoSQL database, provides a mechanism for storing and retrieving unstructured data or data that is not represented in tabular relations in the same way as SQL databases are. Since NoSQL databases were designed to address SQL databases’ scalability issues, they are schema-free and based on distributed systems, making them easier to scale and shard.

It is gaining immense popularity as it is the preferred choice for big data and real-time applications. Since it is schema-free, the data structure is carefully designed before a NoSQL database is created. This makes it highly scalable, flexible and can deal with a variety of data models.


  • It is capable of handling big data.
  • It is schema-free, which makes it flexible to work with any data model.
  • It is built on distributed systems and has low scalability costs because it doesn’t require additional hardware to scale.
  • It has no support for blobs of data such as files or images.
  • Smaller enterprises use them due to their low-cost and high-scalability features.


  • NoSQL’s advantages come at the cost of relaxed ACID characteristics. As a result, NoSQL can only guarantee eventual consistency, which can lead to data loss.
  • It doesn’t have a mature community when compared to SQL databases.
  • Since there is no SQL-like standard language, it makes it difficult to learn APIs for different NoSQL databases.

Different types & some examples of Non-relational databases

Non-relational databases have been divided into four categories:

  1. Column: These databases are similar to that of Relational databases except that these are wide column data tables that are stored and arranged as columns rather than rows. These databases can query huge volumes of data faster than relational databases. Example: Cassandra, Google BigTable, etc.
  2. Document: These databases store data as documents such as like JSON, YAML, or XML. Each document is addressed using a unique key. These databases also provide an API and query language for retrieving documents based on their contents. Example: MongoDB, CouchDB, etc.
  3. Key-value: These databases store data as dictionaries or hashes, where the key is a string and the value might be a string, array, set, etc. Example: Redis, DynamoDB, etc.
  4. Graph: These databases store data in the form of nodes and edges that create a graph. The entities are represented by nodes, while the relationships between the entities are represented by edges. Example: AllegroGraph, Titan, etc.

Which database is preferable?

If you are working on an application that will manage a large volume of structured, semi-structured, and unstructured data, and the major priority of the application is scalability and performance, then a NoSQL database should be used.

If you want your data transactions to be durable and high-secure, and you want to store a large volume of structured data, and also want to use SQL to use complex queries to retrieve information, then a SQL database should be used.