MongoDB vs MySQL: Which database to use

Differences between MongoDB and MySQL#

In this section, we will cover some of the main differences between MongoDB and MySQL.

Data Representation#

MongoDB represents data as JSON documents, whereas MySQL represents data in rows and tables.

Data would like this in MySQL:

{ 
First Name: 'John',
Last Name: 'Doe', 
Employee_ID: 1234, 
Status: 'Active'
}

Data Embedding#

MySQL does not offer any option for nesting or embedding data. You can use JOINs but they may result in larger tables with unnecessary fields. JOINs can also be time-consuming and performance-intensive.

MongoDB allows you to embed related data. You also have the option of referencing data from another document if you feel the document may grow too much. An example includes:

{
    id: 13,
    name: ‘John Doe’,
    age: 23,
    address: {
        City: 'New Jersey,
        Street: 'London',
        Zip_code: 9876
    }
}

Query Language#

MySQL uses SQL, whereas MongoDB uses MQL, the MongoDB query language. We will compare some common database operations on the Employee table in this section.

Selecting data in MySQL

Select * from employee;

Inserting data in MySQL

INSERT INTO employee (employee_id, department, status)
VALUES (12, 'Sales', 'Active');

Updating data in MySQL

UPDATE employee SET department = 'Finance' WHERE employee_id = 14;

Selecting data in MongoDB*

db.find.employee()

Inserting data in MongoDB

db.employee.insert ({employee_id:'12', department:'Sales', status:'Active'})

Updating data in MongoDB

db.employee.update({employee_id::{$eq:14}},{$set{ department:'Finance'}},{multi:true})

Index Optimization#

Both databases use indexes for optimization. If MySQL does not find a relevant index for a query, it searches the entire table.

MongoDB searches through every document in a collection if there are no indexes.

Database Deployment#

MySQL has binaries for most operating systems so it can be deployed natively, MongoDB, on the other hand, is more suited to distributed environments.

Speed and Performance#

Since MongoDB is a NoSQL database, it is faster than MySQL.

Data Grouping#

MongoDB stores documents that belong to a single class or group in a collection. MySQL stores rows of similar types in a table.

MySQL supports master-slave and master-master replication allowing you to reproduce from several master databases in parallel. MongoDB, on the other hand, supports built-in sharding, replication, and auto-elections.

Sharding allows for horizontal scaling, and auto-elections let you set up secondary databases that take over if your primary database fails.

Security#

MySQL uses a privilege-based security model that authenticates users and facilitates them with privileges on specific database operations. On the transport layer, it uses encoded connections between servers and clients.

MongoDB uses role-based authentication with flexible privileges. It uses Transport and Socket Layers for encoding and decoding, ensuring only intended users have access to the database.

Scalability#

MySQL is vertically scalable, meaning you can increase the load on a single server by increasing RAM or CPU specifications. MongoDB is horizontally scalable, meaning you can create a MongoDB cluster with multiple servers by adding more servers to your database.

Support and Documentation#

MySQL offers lifetime support at three levels:

• Premier: Suited for 1-5 years old
• Extended: Suited for 6-8 years old
• Sustain: Suited for 9+ years old

For each level, it offers 24/7 tech support along with access to patches, bug fixes, maintenance releases, and updates. MySQL’s documentation is maintained by the Oracle Corporation.

MongoDB offers enterprise-grade support. This gives you the flexibility to update versions at your own pace. MongoDB’s documentation is maintained by MongoDB, Inc.

When to use MongoDB or MySQL#

When it comes to choosing between the two, there is no clear winner, as both cater to different fields. Your choice will depend on your project needs and goals. In this section, we will look at when you can use MySQL vs. MongoDB.

MySQL is a good choice if:

• You just started your business, and your database won’t scale much.
• Your data structure won’t change for a long time, or you have a fixed schema.
• You have a high transaction rate.
• Data security is your top priority.
• You need better support. MySQL has been around for a long time so, it’s a lot easier to find solutions to common problems

MySQL is a good choice if you are working with a legacy application that requires multi-row transactions and has structured data with a clear schema.

MongoDB is a good choice if:

• You want high data availability along with automatic and instant data recovery.
• You are working with an unstable schema and want to lower the cost of schema migration…
• Your services are cloud-based.
• You want to speed up development.

MongoDB can be the right choice if you are working with real-time analytics, mobile applications, internet of things, etc., where you may have structure or unstructured data that has the potential for rapid growth.

What to learn next#

In this article, we covered the basics of MySQL and MongoDB along with some key differences between the two. There is a lot to learn next, you can start with: vs. non-relational databases

• SQL Joins
• Stored Procedures
• Indexing
• NoSQL
• Key-value stores
• Node.js drivers

You can check out Educative’s An Introductory Guide to SQL to get started on SQL basics. You will cover everything from creating to updating databases, all in a hands-on environment.

Educative’s interactive course, The Definitive Guide to MongoDB is a great place to start with the basics of NoSQL and build up towards advanced topics.

Happy learning!

Continue reading about databases#

• The complete guide to system design in 2022
• MongoDB vs PostgreSQL: What to consider when choosing a database
• Database design tutorial