MongoDB vs MySQL: 7 Critical Differences

on Database Management Systems, MongoDB, MySQL • December 1st, 2021 • Write for Hevo

Every organization needs a Database for storing transactional data, company data, metadata, performing analysis, and much more. Database technologies have evolved over the years and provide a huge range of features to choose from. 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.

Depending on the use case, a Solution Architect or a Developer chooses a Database architecture. This article will highlight the key factors to keep in mind while comparing MongoDB vs MySQL to help you make a decision. 

Table of Contents

What is MongoDB

MongoDB vs MySQL: MongoDB logo
Image source: MongoDB

MongoDB is an Open-Source, Non-Relational Cloud Document Database. It stores data in JSON-like documents. MongoDB is also a Distributed Database which makes it highly scalable, available, and geographically distributable. MongoDB is available for free to learn and develop small applications. You can connect to your MongoDB Database using 10+ programming language drivers(C++, Java, Python, JavaScript, etc). MongoDB also provides end-to-end security and management tooling for automation, monitoring, and backup.

A Record in MongoDB contains field and value pairs similar to JSON objects. Take a look at the image below to understand. It shows an Object with String, Integer, Character, and Array data types.

MongoDB vs MySQL: MongoDB document
Image source: MongoDB

A group of these Objects/ Documents is referred to as a Collection in MongoDB. A Collection contains one or more Documents (analogous to tables in the Database).

MongoDB vs MySQL: MongoDB Collection
Image source: MongoDB

Learn more about MongoDB from their official Documentation.

What is MySQL

MongoDB vs MySQL: MySQL logo
Image source: MySQL

MySQL is an Open-Source, multithreaded, multi-user, Relational Database server. MySQL is a trademark of Oracle corporation. MySQL is available for free if you want to develop small-scale applications. MySQL is scalable, reliable, and easy to use. MySQL can run on a laptop or desktop and like any other Relational Database, it stores data in the form of a table. Each Database consists of a collection of tables. MySQL client programs can be written in C, C++, Eiffel, Java, Perl, PHP, Python, Ruby, and Tcl.

Learn more about MySQL by referring to the official website.

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Key Differences: MongoDB and MySQL

Below is a comparison of MongoDB and MySQL Databases on the basis of 7 key parameters.

MongoDB vs MySQL: Features


  • MongoDB supports joins in queries, multi-Documents ACID transactions, and supports embedded and 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 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 on your Database performance.
  • It is a fault-tolerant Distributed Database with a lot of data recovery options.


  • MySQL is simple and easy to use and anyone with basic SQL knowledge can work with MySQL.
  • MySQL is compatible with a huge number of Operating Systems. 
  • MySQL allows COMMIT and ROLLBACK for transactions. 
  • It has built-in support for optimizing, repairing, and checking tables.
  • 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.

MongoDB vs MySQL: Architecture


MongoDB vs MySQL: MongoDB Nexus Architecture
Image source: MongoDB

MongoDB’s Nexus Architecture design philosophy combines the capabilities of a Relational Database and also tends to the needs of modern-day applications by providing flexible schema, high scalability, and highly available on-globe deployment.


MongoDB vs MySQL: MySQL Storage Architecture
Image source: MySQL

MySQL has a client-server architecture that has storage optimized for multi-threading and high performance. MySQL has documented some measures to optimize the performance of the server. You can read them here.

MongoDB vs MySQL: Query Language


MongoDB uses MongoDB Query Language (MQL), which is rich and expressive. It supports CRUD operations(Create, Read, Update, Delete), data Aggregation, text search, and Geospatial queries. Learn more about MQL here.


MySQL uses Structured Query Language(SQL) like any other Relational Database. SQL has Data Definition Language (CREATE, ALTER, and DROP tables), Data Manipulation Language (INSERT, UPDATE and DELETE rows), Data Transaction Language (COMMIT, ROLLBACK, etc), and Data Control Language (GRANT and REVOKE) command. It also supports joins to fetch data from multiple tables.

MongoDB vs MySQL: Schema Flexibility


MongoDB is amazing for modern-day applications as it offers a flexible schema design that allows you to meet the ever-changing conditions of Big Data applications. With MongoDB, you can easily store and combine any type of data and dynamically modify schema without experiencing application downtime.


MySQL is amazing if you have a predefined and fixed schema. It allows you to maintain consistency in data. It is quite difficult to use MySQL if the needs of your organization require a dynamic schema.

MongoDB vs MySQL: Performance


When it comes to the performance of MongoDB on unstructured data it is relatively very fast when compared to MySQL. The main reason for this is its Documents-based data storage. Performs better than MySQL when working with Objects due to its JSON type Object storage.


MySQL performs great in transactional operations. But when the data volume gets huge you can observe slow performance. The reason is that the tables are stored in a normalized format and to fetch or change data requires it to go through lots of tables hence it increases the load on the server and affects the performance.

MongoDB vs MySQL: Pricing


For small-scale applications on the shared Cloud, MongoDB can be used free of cost on the M0 cluster. There are a lot of factors that decide the pricing tier that would suit you like the type of Cloud, amount of storage, security standards. Cloud MongoDB Database has three pricing tiers- Shared, Dedicated, and Multi-Region. The price estimates of Dedicated and Multi-region tiers are $57/ month and $95/month respectively. Contact the sales team to get an accurate estimate for your use case. Refer to the official website here

For deploying MongoDB in your private Cloud contact the sales team to know about the pricing.


For commercial purposes, MySQL has three pricing editions each with its features and constraints- MySQL Standard Edition which costs $2000 per annum, MySQL Enterprise Edition which costs $5000 per annum, and MySQL Cluster CGE which costs $10,000 per annum. Refer to their features on the official website.

MongoDB vs MySQL: Security


MongoDB provides security features like authentication, access control (user,role-based access control), and encryption(TLS/SSL) for sensitive data. Security features also depend on the pricing tier.


MySQL offers normal encryption and normal security policies for the Standard Edition. But for the other two editions, it offers authentication, TDE, encryption, masking, firewall, and audit.

Disadvantages of Using MongoDB

A few cons of using MongoDB are listed below:

  • The transactions using MongoDB are complex.
  • When it comes to ACID (Atomic, Consistency, Isolation & Durability) properties, MongoDB is not strong compared to many other RDBMS systems.
  • RDBMS doesn’t support any Stored Procedures or functions and fails when it comes to implementing any business logic at the Database level that you can easily achee in other RDBMS systems.

Disadvantages of Using MySQL

A few cons of using MySQL are listed below:

  • If sometimes a server crash happens, it can corrupt the system catalog.
  • Transactions that are related to the catalog are not ACID compliant.
  • Most of the MySQL tables used for the procedure or trigger are pre-locked.


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 Databases are used in specific scenarios (fixed schema constraints). MongoDB Database is used if your application deals largely with Objects and if your requirement is schema flexibility. Also, you can split the responsibilities between MySQL and MongoDB giving you the freedom to exploit both of their features.

The choice between MongoDB and MySQL Databases is challenging and both may suit your requirements. Here’s a summary:

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

Whether you select one or choose a hybrid combination of the two Databases, the success of your application will depend on having access to data transfer tools that can work between these systems and external data sources. Hevo is a No-code Data Pipeline and has awesome 100+ pre-built integrations that you can choose from. Hevo can help you integrate data from MongoDB and MySQL and load them into a Data Warehouse of your choice. It will make your life easier and make data migration hassle-free.

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