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How to connect MongoDB to MySQL:
The Hard Way vs The Easy Way

By Laurent Mauer · October 10, 2022 · 9 min read

Do you want to connect/replicate data from MongoDB to MySQL?

There are many reasons why you might want to do this, including:

  • Pass from an unstructured model to a structured one
  • Dynamic schemas that are more difficult to model in pure NoSQL
  • Backup / Disaster Recovery 

When connecting the two, MySQL will act as a central point for data management and extraction. This can be useful when working on a team of developers and designers. 

This article will guide you through how to connect MongoDB to MySQL with two different methods.

What is MongDB?

MongoDB is a document-oriented database that provides high performance, high availability, and automatic scaling. It stores data as JSON documents, making it easier for developers to store and retrieve data. MongoDB is a popular NoSQL database that many companies have adopted due to its flexibility and scalability.

The following are some of the main features of MongoDB:

  • High Performance: MongoDB provides high performance, with up to 10K operations per second per node, even on commodity hardware. Additionally, it has a built-in aggregation framework that can handle complex queries efficiently.
  • Flexibility: MongoDB supports dynamic schemas and rich data types (such as arrays and embedded documents), which makes it easy to evolve your application without changing the database schema. This allows organizations to rapidly prototype applications without having to make any changes in their existing data models or applications.
  • Scalability: MongoDB scales out horizontally by adding additional nodes for better performance or adding capacity for more users or data, thus improving the performance and reliability of an application by distributing the load across multiple machines or data centers.

What is MySQL?

MySQL is a relational database management system (RDBMS) whose syntax and features are similar to those of Oracle and PostgreSQL. Its name is in honor of the co-founder of Sun Microsystems, Michael “Monty” Widenius.

This is an open source relational database management system (RDBMS) that runs on most operating systems.

It’s free to use and has a rich feature set. The most popular use for MySQL is for web applications, but it can also be used in business-critical applications as well as embedded systems.

MySQL stands out from its competitors mainly because it operates in both relational and non-relational forms, giving developers the ability to choose which form works best for their applications.

In this way, MySQL is able to cater to a number of different purposes from a small business owner who uses it to keep track of customer information at their shop up to massive enterprises like Facebook, Google, Amazon and others.

The main differences between MongoDB and MySQL

This table summarizes the main differences between MongoDB and MySQL: 

Method 1: The Hard Way: Manual ETL Process to Set Up MongoDB to MySQL Integration

The manual process includes the three following steps:

Step 1: Extract Data from MongoDB (using mongoexport Command)

We’ll start by creating a CSV file from an existing Mongo collection with the mongoexport command.

Let’s understand this process with an example.

The database is called purchasedb and the collection name is purchases.

The expected output file is purchases.csv.

The names of the keys that will be exported to CSV will be in the last attribute fields.

This is critical since MongoDB does not maintain a rigid key structure, and it is extremely likely that not all keys will be present in all documents.

The developer must verify that the keys that must be present in the CSV file are defined. 

Mongoexport will not produce an error if there is no such key in the document. It will simply insert a blank value into that column. If you’re not careful, this can have unintended consequences.

Step 2: Create a Product Table in MySQL to store the Incoming Data

Step 3: Load the Exported CSV to MySQL

This completes the process.

These steps may seem simple, but keep in mind that this is a very simplified version of the actual data migration issue.

MongoDB and MySQL are very different databases and there are many factors that can cause unexpected failures in this migration.

Let’s look at some cases where problems can occur when using the above approach.

The manual ETL process is not an efficient solution for integrating MongoDB and MySQL.

It is time-consuming, expensive, and error-prone.

Limitations of Manual ETL process to set up MongoDB to MySQL integration

Here are the main limitations of Manual ETL process to set up MongoDB to MySQL integration:

  • Manual ETL is not scalable. It is difficult to scale the manual ETL process because it depends on the skill level of the person who is doing it. The same logic cannot be used by everyone. So each time a new developer comes in, they have to learn from scratch while they are working on the same task. This increases the time taken for them to complete the task and increases cost as well.
  • Manual ETL process is error-prone and requires more resources like people and hardware infrastructure which need to be maintained regularly just like any other software application in your organization. You start getting problems when there is no one available 24×7 to take care of these things or when there are too many bugs reported for this software application that needs urgent attention from developers.

Method 2: The Easy Way: Using RestApp to pipe Data from MongoDB to MySQL

RestApp is a No Code Data Activation Platform that empowers anyone with an all-in-one solution to connect, model, and sync any data with his favorite tools.

Access to ready-to-use connectors to save time and pain in building them from scratch: Database, data warehouse, business apps, SFTP, GDrive…

The steps to load data from MongoDB to MySQL using RestApp are as follows: 

Connect RestApp to your MongoDB account

  • Step 2: Fill in the required fields and test the connection:
  • Step 3: Choose to use MongoDB connector as an Input (Source):

Et voilà! Your MongoDB connector is up and running!

Connect RestApp to your MySQL account

  • Step 2 – Fill in the required fields and test the connection:

  • Step 3: Choose to use MySQL connector as an Output (Destination):

Et voilà! Your MySQL connector is up and running!

Model and sync your data from MongoDB to MySQL

You can now model and sync your data from MongoDB to MySQL with drag-and-drop SQL & Python built-in functions. 

  • Step 0: Create your model in the Pipelines App

  • Step 1: Retrieve your data from MongoDB with the “Input” function:

  • Step 2: Select the columns you want to replicate in your MySQL database:

  • Step 3: Replicate your data to MySQL with the “Output” function:

Replicate your data to MySQL

In the output section, you have 3 types of syncing:

  • Add data (for unique migration)
  • Add & Update data (periodic migration)
  • Erase & Replace data (migration to fully modify the current destination table)

You’ve now successfully set up RestApp’s MongoDB to MySQL integration!

Bonus: Automate the replication of data from MongoDB to MySQL

Activate your data pipeline through a scheduler to operationalize your data with automation. 

In this example, the pipeline will be automatically synchronized every hour.

You also have access to the logs to verify the authenticity of the automation:


In this article, I introduced you to MongoDB and PostgreSQL and explained their features.

We also described two methods you can use to set up MongoDB and PostgreSQL integration. 

The manual method is effective, but it requires a lot of time and resources. Migrating data from MongoDB to PostgreSQL is a tedious and time-consuming process, but data integration tools like RestApp make this process easy and time-saving.

If you’re interested in starting with connecting all your favorite tools, check out the RestApp website or try it for free with a sample dataset.

Discover the next-gen end-to-end data pipeline platform with our built-in No Code SQL, Python and NoSQL functions. Data modeling has never been easier and safer thanks to the No Code revolution, so you can simply create your data pipelines with drag-and-drop functions and stop wasting your time by coding what can now be done in minutes! 

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Brian Laleye
Brian Laleye
Brian is the co-founder of RestApp. He is a technology evangelist and passionate about innovation. He has an extensive experience focusing on modern data stack.

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