MongoDB to MySQL: 2 Easy Methods for Replication

MongoDB is a NoSQL database that stores objects in a JSON-like structure. It is usually classified as document-oriented storage because of the way it treats objects as documents. Schemaless databases like MongoDB offer unique versatility because of their ability to store semi-structured data.

MySQL, on the other hand, is a structured database with a hard schema. It is a usual practice to use NoSQL databases for use cases where the number of fields will evolve as the development progresses. At some point in time, when the use case matures itself, organizations will notice the overhead introduced because of their NoSQL schema and will want to migrate the data to hard-structured databases with comprehensive querying ability and predictable query performance. 

In this article, you will first learn the basics about MongoDB and MySQL and how to set up MongoDB to MySQL Integration using the two methods easily. You will also explore the limitations of manually setting up MongoDB to MySQL Integration. Read along to decide which method of connecting MongoDB to MySQL is best for you.

What is MongoDB?

MongoDB is a popular open-source, non-relational, document-oriented database. Instead of storing data in tables like traditional relational databases, MongoDB stores data in flexible JSON-like documents with dynamic schemas. This makes it easy to store unstructured or semi-structured data.

Some key features of MongoDB include:

• Document-oriented storage: More flexible and capable of handling unstructured data than relational databases. Documents map nicely to programming language data structures.
• High performance: Outperforms relational databases in many scenarios due to flexible schemas and indexing. Handles big data workloads with horizontal scalability.
• High availability: Supports replication and automated failover for high availability.
• Scalability: Scales horizontally using sharding, allowing the distribution of huge datasets and transaction load across commodity servers. Elastic scalability for handling variable workloads.

What is MySQL?

MySQL is a widely used open-source Relational Database Management System (RDBMS) developed by Oracle. It employs structured query language (SQL) and stores data in tables with defined rows and columns, making it a robust choice for applications requiring data integrity, consistency, and reliability.

Some major features that have contributed to MySQL’s popularity over competing database options are:

• Full support for ACID (Atomicity, Consistency, Isolation, Durability) transactions, guaranteeing accuracy of database operations and resilience to system failures – vital for use in financial and banking systems.
• Implementation of industry-standard SQL for manipulating data, allowing easy querying, updating, and administration of database contents in a standardized way.
• Database replication capability enables MySQL databases to be copied and distributed across servers. This facilitates scalability, load balancing, high availability, and fault tolerance in mission-critical production environments.

Methods to Set Up MongoDB to MySQL Integration

There are many ways of loading data from MongoDB to MySQL. In this article, you will be looking into two popular ways. In the end, you will have a good understanding of each of these two methods. This will help you to make the right decision based on your use case:

• Method 1: Using Hevo Data to Set Up MongoDB to MySQL Integration
• Method 2: Manual ETL Process to Set Up MongoDB to MySQL Integration

Prerequisites

• MongoDB Connection Details
• MySQL Connection Details
• Mongoexport Tool
• Basic understanding of MongoDB command-line tools
• Ability to write SQL statements

Method 1: Using Hevo Data to Set Up MongoDB to MySQL Integration

Hevo Data, a No-code Data Pipeline, helps you directly transfer data from MongoDB and 150+ other data sources to MySQL and other Databases, Data Warehouses, BI tools, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss.

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

Step 1: Configure MongoDB as your Source

• Click PIPELINES in the Navigation Bar.
• Click + CREATE in the Pipelines List View.
• In the Select Source Type page, select MongoDB as your source.
• Specify MongoDB Connection Settings as following:

Step 2: Select MySQL as your Destination

• Click DESTINATIONS in the Navigation Bar.
• Click + CREATE in the Destinations List View.
• In the Add Destination page, select MySQL.
• In the Configure your MySQL Destination page, specify the following:

Hevo automatically flattens all the nested JSON data coming from MongoDB and automatically maps it to MySQL destination without any manual effort. For more information on integrating MongoDB to MySQL, refer to Hevo documentation.

Here are more reasons to try Hevo to migrate from MongoDB to MySQL:

Method 2: Manual ETL Process to Set Up MongoDB to MySQL Integration

MongoDB and MySQL are extremely different databases with different schema strategies. This means there are a lot of things to consider before moving your data from a Mongo collection to MySQL. The simplest of the migration will contain the few steps below.

Step 1: Extract data from MongoDB in a CSV file format

Use the default mongoexport tool to create a CSV from the collection.

mongoexport --host localhost --db classdb --collection student --type=csv  --out students.csv --fields first_name,middle_name,last_name, class,email

In the above command, classdb is the database name, the student is the collection name and students.csv is the target CSV file containing data from MongoDB. An important point here is the –field attribute. This attribute should have all the lists of fields that you plan to export from the collection. If you think about it, MongoDB follows a schema-less strategy and there is no way to ensure that all the fields are there in all the documents.

If MongoDB was being used for the purpose it was designed for, there is a big chance that not all documents in the same collection have all the attributes. Hence while doing this export, you should ensure these fields are in all the documents. If the fields are not in all documents, MongoDB will not throw an error but will populate an empty value in its place.

Step 2: Create a student table in MySQL to accept the new data.

Use the Create table command to create a new table in MySQL. Follow the code given below.

CREATE TABLE students ( id INT(6) UNSIGNED AUTO_INCREMENT PRIMARY KEY, firstname VARCHAR(30) NOT NULL, middlename VARCHAR(30) NOT NULL, lastname VARCHAR(30) NOT NULL, class VARCHAR(30) NOT NULL, email VARCHAR(30) NOT NULL, )

Step 3: Load the data into MySQL

Load the data into the MySQL table using the below command.

LOAD DATA LOCAL INFILE 'students.csv' INTO TABLE students FIELDS TERMINATED BY ','  ENCLOSED BY '"' LINES TERMINATED BY 'n' (firstname,middlename,lastname,class,email)

You have the data from MongoDB loaded into MySQL now.

Another alternative to this process would be to exploit MySQL’s document storage capability. MongoDB documents can be directly loaded as a MySQL collection rather than a MySQL table. The caveat is that you cannot use the true power of MySQL’s structured data storage. And in most cases, that will be why you moved the data to MySQL in the first place. 

However, the above steps only work for a limited set of use cases and do not reflect the true challenges in migrating a collection from MongoDB to MySQL. Let us look into them in the next section.

Limitations of Manually Setting Up MongoDB to MySQL Integration

Though the manual method of setting up MongoDB to MySQL was effective, this method has numerous limitations. Below are some of the limitations associated with manually setting up MongoDB to MySQL Integration:

1. In real life, there will be hundreds of fields in a collection, and creating the first command(the first step) will be a pain when trying to write all the fields manually.
2. This approach needs you to have access to an instance with enough storage space to store the whole contents of the collection and then execute the LOAD DATA command.
3. In MongoDB use cases, typically, there will be many attributes that do not exist in all the documents. This method will populate empty values in such cases. This is not a desirable behavior and in most cases, you will need to write a custom script to handle this.
4. This method is suitable for a first-time bulk load, but if your use case needs frequent syncing, it would be tough to handle the duplicate data rows and scheduling. 
5. This is going to be an extremely time-consuming process if the source collection is large. If MongoDB is being used for serving a live website or mobile app, the developer will need to build additional throttling logic so that the incoming traffic is not affected.
6. You could also end up in trouble if the fields inside your MongoDB have arrays as their values. These will need to be specifically handled using a script since the simple CSV export can lead to unexpected results here. 

A solution to all these complexities will be to use a third-party cloud-based ETL tool like Hevo. Hevo can mask all the above concerns and provide an elegant migration process for your MongoDB collections. 

Use Cases of MongoDB to MySQL Migration

• Structurization of Data: When you migrate MongoDB to MySQL, it provides a framework to store data in a structured manner that can be retrieved, deleted, or updated as required. 
• To Handle Large Volumes of Data: MySQL’s structured schema can be useful over MongoDB’s document-based approach for dealing with large volumes of data, such as e-commerce product catalogs. This can be achieved if we convert MongoDB to MySQL.  

MongoDB compatibility with MySQL

Although both MongoDB and MySQL are databases, you cannot replace one with the other. A migration plan is required if you want to switch databases. These are a few of the most significant variations between the databases.

Querying language

MongoDB has a different approach to data querying than MySQL, which uses SQL for the majority of its queries. You may use aggregation pipelines to do sophisticated searches and data processing using the MongoDB Query API. It will be necessary to modify the code in your application to utilize this new language.

Data structures

The idea that MongoDB does not enable relationships across data is a bit of a fiction. Nevertheless, you may wish to investigate other data structures to utilize all of MongoDB’s capabilities fully. Rather than depending on costly JOINs, you may embed documents directly into other documents in MongoDB. This kind of modification results in significantly quicker data querying, less hardware resource usage, and data returned in a format that is familiar to software developers.

Conclusion

This article gives detailed information on migrating data from MongoDB to MySQL. It can be concluded that Hevo seamlessly integrates with MongoDB and MySQL, ensuring that you see no delay in setup and implementation. Hevo will ensure that the data is available in your database in real-time. Hevo’s real-time streaming architecture ensures you have accurate, latest data in your database.

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Businesses can use automated platforms like Hevo Data to export MongoDB to MySQL and handle the ETL process. It helps you directly transfer data from a source of your choice to a Data Warehouse, Business Intelligence tools, or any other desired destination in a fully automated and secure manner without having to write any code and will provide you with a hassle-free experience.

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Share your experience of loading data from MongoDB to MySQL in the comment section below.