[Series] Data teams
How to connect MongoDB to MySQL:
The Hard Way vs The Easy Way
By Laurent Mauer · October 10, 2022 · 10 min read
Are you interested in replicating or connecting data from MongoDB to MySQL? There are several reasons why you may want to do this, including the need to move from an unstructured model to a structured one, the difficulty in modeling dynamic schemas in pure NoSQL, and the need for backup and disaster recovery.
When connecting these two databases, MySQL can serve as a centralized point for data management and extraction. This can be especially useful for teams of developers and designers.
In this article, we will guide you through two different methods for connecting MongoDB to MySQL.
Summary
What is MongoDB?
MongoDB is a well-known NoSQL database that uses a document-oriented approach for storing and retrieving data. Its ability to provide high performance, high availability, and automatic scaling makes it a popular choice among many companies. By storing data as JSON documents, MongoDB makes it easier for developers to work with data.
One of the main advantages of MongoDB is its high performance, which can handle up to 10,000 operations per second per node, even on inexpensive hardware. MongoDB also includes a built-in aggregation framework that can efficiently manage complex queries.
Another benefit of MongoDB is its flexibility. The database supports dynamic schemas and rich data types, such as arrays and embedded documents. This feature allows developers to quickly prototype and evolve their applications without the need to modify the database schema or existing applications.
Finally, MongoDB is highly scalable, allowing organizations to easily add additional nodes for better performance or capacity. By distributing the load across multiple machines or data centers, MongoDB can improve application performance and reliability.
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.
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The main differences between MongoDB and MySQL
This table summarizes the main differences between MongoDB and MySQL:
Source: geeksforgeeks.org
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 the mongoexport command
To start, we will use the mongoexport command to create a CSV file from an existing Mongo collection. Let’s walk through this process using an example.
we have a database named “purchasedb” and a collection called “purchases”.
Our expected output file will be named “purchases.csv”.
It is important to note that the names of the keys to be exported to the CSV file will be located in the last attribute fields.
Since MongoDB does not enforce a strict key structure, it is likely that not all keys will be present in all documents.
Therefore, it is the developer’s responsibility to ensure that the keys necessary for the CSV file are defined.
If a key is not present in a document, mongoexport will insert a blank value in that column without producing an error.
This can have unintended consequences if the developer is not careful.
Step 2: Establish a product table within MySQL that will be used to store the incoming data
Step 3: Load the previously exported CSV file into MySQL
That concludes the data migration process, but it’s important to note that this simplified version may not account for all factors that can cause unexpected failures in the migration from MongoDB to MySQL.
MongoDB and MySQL are fundamentally different databases, which can make the migration process complex.
As a result, there are certain scenarios where problems can arise when using the above approach.
For example, the manual ETL process used in this approach is not considered an efficient solution for integrating MongoDB and MySQL due to its time-consuming nature, potential expense, and susceptibility to errors.
Limitations associated with using a manual ETL process to establish integration between MongoDB and MySQL
Listed below are the key limitations of utilizing a manual ETL process to set up an integration between MongoDB and MySQL:
- The manual ETL process is not easily scalable because it relies heavily on the expertise of the individual performing the task. Since the same approach may not be universally applicable, new developers are required to learn from scratch when working on the same task, resulting in longer completion times and higher costs.
- The manual ETL process is prone to errors and requires additional resources, such as personnel and hardware infrastructure, which must be regularly maintained like any other software application in your organization. When there is no one available around the clock to handle these matters or when numerous bugs are reported for this software application that require immediate attention from developers, issues can arise.
Method 2: A Simpler Approach: Utilizing RestApp to Transfer Data from MongoDB to MySQL.
RestApp is a platform that enables data activation without the need for coding, allowing anyone to connect, model, and synchronize data with their preferred tools. It includes pre-built connectors for databases, data warehouses, business applications, SFTP, and GDrive, which can save time and effort in developing them from the ground up.
Here are the steps to follow in order to load data from MongoDB to MySQL using RestApp:
Connecting RestApp to your MongoDB account
- Step 1: Click on “MongoDB” connector (documentation):
- 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 1 – Click on “MySQL” connector (documentation):
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:
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:
Conclusion
In this article, we have provided an introduction to MongoDB and PostgreSQL, and outlined their key features. Additionally, we have explained two methods for establishing integration between MongoDB and PostgreSQL.
While the manual approach can be effective, it is time and resource-intensive. Migrating data from MongoDB to PostgreSQL can be a tedious and time-consuming process. However, there are data integration tools, such as RestApp, that make this process much simpler and more efficient.
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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