Difference Between MongoDB, MySQL, and PostgreSQL

March 12th, 2022

Evgenia Kuzmenko KITRUM Brand ManagerEvgenia Kuzmenko

You’re probably always confused and indecisive every time you need to choose a database technology for your development project. Well, it’s not your fault; we have all been there. The multiplicity of Database Management Systems (DBMS) has left us developers spoilt for choices. In a recently compiled list of most and not all DBMS, we counted 52 of them, 10 of which are quite popular.

Before we go ahead, let us define a DBMS is for the non and new developers.

A database management system is a program that lets you manage a web system’s data storage processes. Data is interpreted, modified, and extracted using DBMS access. 

This brings us to the crux of the discussion; a comparison of three very popular DBMS you are familiar with; MySQL, PostgreSQL, and MongoDB.

You have at some point heard or read varying opinions on which of the mentioned DBMS is better for a particular project. We are not telling you which is better because, realistically, no one is completely better than the other; they just all have their strengths and weaknesses. So we will focus on the facts, tell you their strengths and where they perform better.

So take away all the noises and opinions you have heard over time, focus on the facts and let’s ride.


In today’s big data world, MySQL is one of the most well-known database technologies. It is frequently referred to as the most widely used database. MySQL is the most used data storage solution, according to a recent developer survey. With 55.6 percent of the respondents choosing it. 

MySQL is designed to be open-source and so has a very huge and active community. It was built using the C and C++ programming languages. It is compatible with various operating systems, including Linux, OS X, Solaris, and Windows.

Benefits of MySQL

Open Source and Free

MySQL is open-source, and of course, we know that open source programs with an active community have the advantage of continuous development and update. Also, the DBMS has a community version that is available for free installation. However, the free version doesn’t have as many features as the paid ones, but it is still efficient for smaller projects.

Simple and Flexible

The architecture and operations of MySQL are quite simple. It ensures comprehensive operations, even for large-volume projects, thanks to better security. Debugging can also be done more quickly.

Good Performance

MySQL’s most recent version was created with speed and efficiency. Even for E-commerce websites, the database is quite promising due to its high performance and good memory cache. It can address multiple (up to a million) requests at once.

Wide Compatibility

Despite its popularity as a database for web applications, MySQL was created to work with a wide range of technologies and systems. The RDBMS is compatible with various computing platforms, including Unix-based operating systems like Linux and Mac OS and Windows.

Drawbacks to MySQL

Here are a few drawbacks to MySQL

Limited Open-source activity

Although MySQL is an acclaimed open-source database, it no longer seems that way in practice. Since coming under Oracle’s control, MySQL now has private closed-source modules. Open-source developers are getting disenchanted with the project because of Oracle’s Purported development stumbling blocks and refusal to disclose test cases for defects and security updates.

SQL standards are not completely followed.

MySQL is based on the Structured Query Language(SQL) program, which has its unique rules and standards. MySQL does not completely adhere to SQL standards. It rather has its unique structure and extensions.


PostgreSQL is another popular DBMS that shares a lot of similarities with MySQL. In a recent survey, it was selected as the second most popular DBMS behind MySQL. Developers also chose it as the second most loved and second most wanted DBMS behind Redis and MongoDB.

PostgreSQL is a relational database management system (DBMS) that creates more complex data structures by combining defined objects and table procedures. Its goal is to improve the adherence and expansibility of the standards. As a result, it can handle any workload, whether for a single machine or a complicated application.

It was developed as an open-source DBMS. This DBMS was created using the C programming language and is compatible with Microsoft, iOS, Android, NetBSD, Linux, and various other platforms.

Benefits of PostgreSQL

Enhanced Scalability

PostgreSQL is optimized for quick and continuous scalability, and this quality gives it an edge over MySQL. Because of its high scalability capabilities, PostgreSQL can be deployed in large corporations and for high-demanding projects.

Its Completely Open-source

PostgreSQL arguably has the best and most active open-source ideology. It offers organizational efficiency and limitless growth opportunities. Users of PostgreSQL can also participate actively in the community by posting and sharing bugs and problems.

Wide support for custom data

PostgreSQL is popularly known to have good operational support for noSQL data modules. It supports a wide range of data types, including JSON, XML, H-Store etc., by default.

Collaborate efficiently with other tools

There is a wide range of database management tools that complements DBMS. Unfortunately, many DBMS have limited integration ability. PostgreSQL solves this problem by integrating effortlessly and efficiently with many other independent tools.

Drawbacks to PostgreSQL

Quite Slow

People who use Postgres run into a variety of performance concerns as well as backup recovery issues. Frequently, you’ll have a slow query and see that your database environment’s performance has degraded. Due to its relational database structure, Postgres must start with the first row and then scan through the entire table to identify the relevant data while looking for a query. As a result, it’s slower, especially when there’s a lot of data in the rows and columns of a table with many variables to compare.

Incomplete Documentation

Even though PostgreSQL has a big community and offers excellent assistance, the documentation remains irregular and incomplete. Due to the scattered nature of the PostgreSQL community, documentation for all Postgre features does not adhere to the same standards.

There are no reporting or auditing tools.

There is a higher chance that engineers would miss PostgreSQL failure due to the lack of auditing tools. Using this tool requires carefulness.


MongoDB is a non-relational data storage management system that processes and stores large amounts and varying data types using flexible documents rather than tables and rows. MongoDB does not require a relational data storage system because it is a NoSQL solution; hence it offers an extensible data storage format that allows you to manage multiple data types with ease.

MongoDB is developed and managed by MongoDB.Inc, which was first released in February 2009. It is widely used because it offers flexibility by supporting all popular programming languages.

Benefit of MongoDB

Operational efficiency

The rapid and simple operations are one of MongoDB’s advantages gained from its Non SQL nature. Data can be instantly inputted, saved, and retrieved from the database without the need for further validation. It prioritizes RAM utilization, so records can be accessed quickly without compromising data quality.

Support for multiple languages

MongoDB’s multi-language support is one of its best features. MongoDB has been updated through several versions and is still being developed, with driver support for prominent programming languages such as Python, PHP, Ruby, C++, Scala, JavaScript, etc.

Interoperability with various data formats.

MongoDB works well with a variety of database administration programs, including SQL and NoSQL.

Drawback of MongoDB

Requires a large amount of memory space

The operations of MongoDB require a lot of memory space for efficiency. This DBMS also remembers all of the key names for each value pair, contributing to its memory consumption.

Interpreting into different query languages is a difficult process.

Because MongoDB was not designed to execute relational data models from the start, performance may suffer in these situations. Furthermore, the conversion of SQL to MongoDB queries necessitates additional steps to use the engine, potentially causing delays.

Nesting Space Is Limited

Nesting documents for more than 100 levels is not possible.

MySQL vs PostgreSQL vs MongoDB


It’s difficult to choose a suitable data management program for your operating system. Each one has its distinct advantage, and the type of data you need to store determines which one you choose.

Looking for experienced DevOps to manage your Database?