Two very popular Database technologies that have their own demand are MongoDB and MySQL.

MongoDB is the popular NoSQL Database and MySQL is the popular SQL Database.

Are you confused between MongoDB vs MySQL decision? If yes, then this article highlights the key differences between MongoDB and MySQL to help you choose the right Database for your business.

Key Differences: MongoDB vs MySQL

Relational/ Non-RelationalNon-Relational DatabaseRelational Database
Data TypeUnstructured and/or Structured DataStructured Data
Data RepresentationMongoDB represents data as JSON documentsMySQL represents data in tables and rows
Defining SchemaNo need to define Schema in MongoDBYou need to define tables and columns in MySQL
JOIN OperationsNot SupportedMySQL supports JOIN operations
Query LanguageJavaScriptSQL
PriorityIf you have multiple cloud-based services When the priority is security
Scalability Easily ScalableScalability is limited

What are SQL and NoSQL Databases?

SQL (Relational) Databases

  • SQL(Structured Query Language) is used in Relational Databases (SQL Databases) to create, update and delete database objects. It uses tables to define relationships while following strict ACID(Atomic, Consistency, Isolation & Durability) properties. 

NoSQL (Non-Relational) Database

  • NoSQL Databases do not follow a structured data format. These are non-tabular databases that can easily scale with large volumes of data and high user loads.

Want to explore the key differences between NoSQL and SQL Databases? Read SQL vs NoSQL Databases: 5 Critical Differences to gain a better understanding.

What is MongoDB?

  • MongoDB is an Open-Source, NoSQL Database. It stores data in JSON-like documents. It is created, maintained, and managed by MongoDB.Inc under the SSPL(Server Side Public License) license.
  • MongoDB is also a Distributed Database which makes it highly scalable, available, and geographically distributable. It is available for free to learn and develop small applications.

What is MySQL?

  • MySQL is an Open-Source, multithreaded, multi-user, Relational Database. It is a trademark of Oracle Corporation and is available for free if you want to develop small-scale applications.
  • MySQL is scalable, reliable, and easy to use.
  • You can run it on a laptop or a desktop. It uses a basic Client-Server Model to assist users in managing Relational Databases, or data stored in rows and columns across tables.
  • MySQL client programs can be written in C, C++, Eiffel, Java, Perl, PHP, Python, Ruby, and Tcl.

Want to explore more about MySQL? Refer to the MySQL official website.

Pros & Cons of MongoDB

  • The schema of MongoDB isn’t predefined. Its dynamic schematic architecture allows it to operate with unstructured data.
  • As MongoDB is schemaless, expansion plans are flexible, and extra systems and RAM can be readily added.
  • MongoDB supports joins in queries, multi-Documents ACID transactions, and supports embedded & reference relationships between Documents.
  • It has a very powerful and expressive query language that allows you to search, sort, and filter using any field.
  • Its rich JSON-like Documents allow flexible and dynamic schemas.
  • MongoDB Atlas provides a Multi-Cloud Database service on AWS, Google Cloud, and Azure for the modern Cloud era.
  • It provides on-demand scaling, resource optimization tools, and real-time insights intoon your Database performance.
  • It is a fault-tolerant Distributed Database with a lot of data recovery options.
  • It uses a document-based query language that is nearly as strong as SQL to allow dynamic queries on documents. Check out how you can Conduct MongoDB Query Performance Analysis easily.

Pros & Cons of MySQL

  • MySQL is simple and easy to use and anyone with basic SQL knowledge can work with MySQL.
  • MySQL allows COMMIT and ROLLBACK for transactions. 
  • It has built-in support for optimizing, repairing, and checking tables.
  • MySQL has a large user- community.
  • MySQL is extremely versatile since it supports a wide variety of embedded applications.
  • In MySQL, all passwords are encrypted and it also provides host-based authentication and is very secure.
  • Its multi-threaded design with kernel threads allows you to work on multiple CPUs and implements in-memory hash tables to optimize performance.
  • Supports both transactional and non-transactional storage.

Use Cases of MongoDB

MongoDB is used by companies such as IBM, Oracle, Zendesk, Sony, Intercom, and others. Here are a few of MongoDB’s most well-known use cases:

  • Aadhar: Aadhar is India’s Unique Identification Project and the world’s largest biometric database. MongoDB is one of the databases it utilizes to store more than 1.2 billion people’s biometric and demographic data.
  • eBay: It is a B2C and C2C eCommerce corporation that employs MongoDB for a variety of projects including search recommendations, cloud management, and metadata storage.

Applications of MySQL

MySQL has been around for nearly two decades and has provided enterprises all around the world with the simplicity of storing enormous amounts of data. Here are some of MySQL’s applications:

  • Sites with a high volume of visitors, such as e-commerce or social sites.
  • Sites that need stringent security standards such as government-based and compliance-heavy sectors.

Use Cases of MySQL

Airbnb, NASA, YouTube, Netflix, Pinterest, Drupal, Joomla, and other notable enterprises use MySQL. Here are a few of the most common MySQL use cases:

  • Wikipedia: Wikipedia, a free web encyclopedia runs on MySQL to keep up with the rising user base. MySQL keeps the page up to date, handles content and visitors, and allows for thousands of additions and modifications.
  • Twitter: T-bird is being used by Twitter to shift away from temporal sharding for tweet storage and toward a more distributed technique. T-bird is based on Gizzard, which employs MySQL.

Frequently Asked Questions (FAQs)

Is MongoDB easier than MySQL?

  • MongoDB’s schemaless nature makes it simple to create and upgrade applications over time, without the need for difficult and costly schema migration processes as you would with a relational database.
  • In comparison to MySQL, there will be a significant performance increase. 
  • MySQL, on the other hand, has a larger online community since it has been around longer. Hence, it will be easier to debug your code or get answers easily.

Should I Use MySQL or MongoDB?

Use MySQL when:

  • You have structured data and need a traditional relational database.
  • You’re just getting started and don’t expect your database to grow much,
  • Data security is a high priority.

Use MongoDB when:

  • Your data is unstructured and dynamic, or if you can’t pre-define your schema.
  • You want high data availability with automated, quick, and immediate data recovery.
  • You plan to scale up in the future. MongoDB includes a built-in sharding option.

Can I Set Up a MongoDB MySQL Integration?

  • There are many ways of loading data from MongoDB to MySQL. You can use a manual ETL Process to Set Up MongoDB MySQL Integration using the Mongoexport tool.
  • In addition, you can use an automated Data Pipeline platform like Hevo that can move your data between MongoDB and MySQL very quickly without writing a single line of code. It is simple, hassle-free, and reliable.

Find out more about Connecting MongoDB to MySQL using two 2 Easy Methods.


  • We hope that the comparison of MongoDB vs MySQL has given you a good understanding of the two Database Management Systems. 
  • Both MongoDB and MySQL are great in their own way. While it may seem that MongoDB Databases save a lot of time in Database definition initially in the development process, the fact remains that a well-defined Database schema with MySQL can give a sizable performance advantage in some cases.
  • Eventually, MySQL is used in specific scenarios (fixed schema constraints). 

Now that you are aware of the differences between MongoDB and MySQL and also have an understanding of why how data replication can help, can read these blogs on replicating data from both the databases:

Do let us know your thoughts about this blog and if you know any other differences in the comments 😊

Easha Meher
Former Research Analyst, Hevo Data

Easha is a programming enthusiast having experience in automated test script creation, regression testing, and integration projects like Thyrocare Integration. She has a batchelor's degree in Computer Science and is keenly interested in creating technical articles related to data engineering that help people solve day to day problems.

No-code Data Pipeline for MongoDB and MySQL