Relational Databases vs. Non-Relational Databases: Pros, Cons and Examples

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Data serves as the root cause for modern technological structures. It means that it also requires adequate storage and management. After all, data is here to stay, which can bring in several problems. We must assign them to different categories to understand how effectively we can solve each problem.

This is where relational and non-relational databases come into the picture. These databases are equipped with robust solutions that help carefully organise, access, and extract data. 

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Whether you’re looking for a place to store simple or complex models or assign data to each category, databases can be a handy solution.

This blog will look into the pros, cons, and examples of the two most common databases. We will also examine the standard features and urge our readers to choose what's best suited for their project. 

Additionally, we will see how a full stack development course can help us understand databases. Let's get started!

What are Relational and Non-Relational Databases? 

A database collects data accessed, managed, and updated to meet the immediate need. As a Java full stack developer, storing data in a unified database is vital, which can help address them efficiently.

A database makes it easier for organisations to access and restrict access to specific files at a point. This data is then used in different organisations, including education centres and small to large-sized businesses.

Among the many databases that have made their way into the mainstream system, relational and non-relational databases rank at the top.

History of Relational and Non-Relational Databases

The history of these two popular databases dates back to 1970 when IBM's lead computer scientist. Edgar F. decided to publish an academic paper hoping to remodel data in a new and more efficient way. He named it 'A Relational Model of Data for Large Shared Banks.'

 Another attempt was made in 1998 with Carlo Strozzi when he decided to use the term 'relational' in NoSQL. 

Similarly, in 2009, Johan Oskassin and Eric Evans used the reversal term 'non-relational' database in the SQL server. Gradually, it became relevant and has been adopted as a database management model. 

A recent report published by Statista in 2022 establishes that Oracle ranks as the most popular in terms of relational DBMS (Database Management Systems). This is evident in its 1266.89 position as seen in the report.

As a Java full stack developer, it is vital to experiment with the different databases before moving to the one best for the task.

Relational Databases

A relational database refers to a database type that enables storing, organising, and managing data with the help of tables. 

Relational data is often structured with the help of tables assembled using rows and columns for better representation. It allows linking data from one table to another or multiple tables simultaneously.

A table can hold up to one data entry or object simultaneously. The columns help put a data store and store. The rows, on the other hand, link the record with data points. A schema also exists, defined as the relationship between a table and another table. 

This connection is called 'relationships', which is then put forth with the help of keys —both primary and foreign. 


The advantages of using the relational database are as follows -

  • Object-oriented programming - As it is mechanised to assist in Object-oriented programming, accessing relational databases is extremely quick and easy.
  • Data storage - As tables deal with a large amount of data, relational databases are a perfect space for all sorts of structured, semi-structured, and unstructured data.
  • Schema requirement - While schemas can be implemented, it is also not necessary at the same time, making them highly scalable.
  • Simple structure - Due to its unilateral approach, relational databases perform efficiently at a reasonable pace.


Let's have a look at the restrictions of relational databases.

  • Data redundancy - Inconsistency occurs due to the same data stored in several tables in the database, which can serve as a pathbreaker.
  • Transaction processing - Transactions aren't a strong suit for relational databases as they require complex SQL queries. When dealing with a considerable amount of data, the system can slow down.
  • Complexity - Relational databases can be challenging to design due to multiple relationships and entities.
  • Scalability - As the database is limited, adding hardware resources can be tricky. It can limit the performance of the system.

Non-relational databases 

Non-relational databases are distributed structures that redefine the traditionally used tabular data storage structures. These databases utilise newer formats such as documents, key-value pairs, wide-column stores, and graphs to offer more flexibility.

NoSQL databases or non-relational databases offer a range of benefits, including better scalability, non-complex structures, and faster performance. 

This database type is well-suited for building web and mobile applications and big data analytics. A Java full stack development course can be beneficial for understanding more about non-relational databases.


Here are the advantages of working with a non-relational database.

  • Flexibility - Non-relational databases come with flexibility due to the absence of a predefined schema. 
  • Scalability - These databases are highly scalable and designed to store large amounts of data, making them the ideal space for e-commerce websites.
  • Cost-effective - This database doesn't require an additional hardware or software set-up making it ideal for startups and small businesses to cut down on operating costs.
  • Higher efficiency - Due to the absence of schemas and queries, they are easier to maintain and perform faster and more efficiently than relational databases.


A Java full stack developer must understand each database's limitations, and it is important to note these points.

  • Poor scalability - Non-relational databases are designed to be scaled easily, making it harder to maintain large amounts of data.
  • Limited data integrity - Relational databases have a higher up in data integrity. Non-relational databases' features make it challenging to maintain data accuracy.
  • Query performance - Regarding queries, non-relational databases perform slowly, which can result in poor performance.
  • Complexity - Compared to relational databases, non-relational databases have more capacity making them complex data holders. 

Examples of Relational & Non-Relational Databases 

Relational Databases have been in the news for quite some time due to multiple uses. Several servers, including Microsoft SQL Server and PostgreSQL have taken to the relational database system. 

Simultaneously, non-relational databases are implemented in several areas involving column stores and document-oriented databases. A full stack development course can help you get a hands-on approach to the different kinds of databases.

The table below differentiates non-relational from relational databases.

Relational Database Non-Relational Databases
MySQL Couchbase
SQLite Amazon DynamoDB
MariaDB Oracle Berkeley DB
Microsoft Access MongoDB
Apache Derby Cassandra
IBM DB2 Amazon ElastiCache
H2 Database Entry Amazon SimpleDB
PostgreSQL Huawei Cloud GES
Azure SQL InterSystems Caché
CloudSQL AstraDB


Both relational and non-relational databases have their advantages and drawbacks. Relational databases suit complex data-based applications, whereas non-relational databases are designed for systems holding large amounts of unstructured data. 

A full stack developer certification can be achieved with a decent understanding of the benefits and disadvantages of both databases. It can also make it easier to access both databases while also absorbing the ins and outs of the system.

Grow your career now! A Java full stack Java developer can make the most of their projects using these databases. To understand how it can be a valuable addition to your skill set, opt for the course today. 

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