Moving Data from MongoDB to MySQL: 2 Easy Methods

MongoDB is a NoSQL database that stores objects in a JSON-like structure. Because it treats objects as documents, it is usually classified as document-oriented storage. Schemaless databases like MongoDB offer unique versatility because they can 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.
• When the use case matures, organizations will notice the overhead introduced by their NoSQL schema. They 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 easily set up MongoDB to MySQL Integration using the two methods.

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, making 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 understand each of these two methods well. This will help you to make the right decision based on your use case:

Prerequisites

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

Method 1: Using CSV File Export/Import to Convert MongoDB to MySQL

MongoDB and MySQL are incredibly different databases with different schema strategies. This means there are many 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 consider it, MongoDB follows a schema-less strategy, and there is no way to ensure that all the fields are present in all the documents.
• If MongoDB were being used for its intended purpose, 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 they are not, MongoDB will not throw an error but will populate an empty value in their 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. In most cases, that is 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 Using the CSV Export/Import Method | Manual setting up

1. Data Structure Difference: MongoDB has a schema-less structure, while MySQL has a fixed schema. This can create an issue when loading data from MongoDB to MySQL, and transformations will be required.
2. Time-Consuming: Extracting data from MongoDB manually and creating a MySQL schema is time-consuming, especially for large datasets requiring modification to fit the new structure. This becomes even more challenging because applications must run with little downtime during such transfers.
3. Initial setup is complex: The initial setup for data transfer between MongoDB and MySQL demands a deep understanding of both databases. Configuring the ETL tools can be particularly complex for those with limited technical knowledge, increasing the potential for errors.

Method 2: Using Hevo Data to Set Up MongoDB to MySQL Integration

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

Step 1: Configure MongoDB as your Source

Step 2: Select MySQL as your Destination

Hevo automatically flattens all the nested JSON data coming from MongoDB and automatically maps it to MySQL destination without any manual effort. 

You can also learn about How to Connect MongoDB Atlas to MySQL

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

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.

Additional Resources for MongoDB Integrations and Migrations

• Connect MongoDB to Snowflake
• Connect MongoDB to Tableau
• Sync Data from MongoDB to PostgreSQL
• Move Data from MongoDB to Redshift
• Replicate Data from MongoDB to Databricks

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.

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. So, to enjoy this hassle-free experience, sign up for our 14-day free trial and make your data transfer easy!

Also, check out our unbeatable pricing for the best plan that fits your needs.

FAQ on MongoDB to MySQL