Two of the most popular database technologies today are MongoDB and MySQL, each with its own strengths and use cases. While MongoDB is a leading NoSQL database known for its flexibility, MySQL remains a top choice among SQL databases for structured data management.
If you’re torn between choosing MongoDB or MySQL, don’t worry! This article breaks down the key differences between these two databases to help you decide which one aligns best with your business needs.
Key Differences: MongoDB vs MySQL
| Parameter | MongoDB | MySQL |
|---|
| Relational/ Non-Relational | Non-Relational Database | Relational Database |
| Data Type | Unstructured and/or Structured Data | Structured Data |
| Data Representation | MongoDB represents data as JSON documents | MySQL represents data in tables and rows |
| Defining Schema | No need to define Schema in MongoDB | You need to define tables and columns in MySQL |
| JOIN Operations | Not Supported | MySQL supports JOIN operations |
| Query Language | JavaScript | SQL |
| Priority | If you have multiple cloud-based services | When the priority is security |
| Scalability | Easily Scalable | Scalability is limited |
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What are SQL and NoSQL Databases?
SQL (Relational) Databases
- SQL(Structured Query Language) is used in Relational Databases (SQL Databases) to create, update and delete database objects. It uses tables to define relationships while following strict ACID(Atomic, Consistency, Isolation & Durability) properties.
NoSQL (Non-Relational) Database
- NoSQL Databases do not follow a structured data format. These are non-tabular databases that can easily scale with large volumes of data and high user loads.
Want to explore the key differences between NoSQL and SQL Databases? Read SQL vs NoSQL Databases: 5 Critical Differences to gain a better understanding.
What is MongoDB?
MongoDB is an open-source NoSQL database that stores data in JSON-like documents, making it highly flexible and efficient. Created and managed by MongoDB, Inc., it operates under the SSPL (Server Side Public License) license. As a distributed database, MongoDB is designed for high scalability, availability, and geographic distribution, making it ideal for modern applications. Best of all, it’s free to use for learning and developing small-scale applications.
What is MySQL?
MySQL is an open-source, multithreaded, multi-user relational database that is a trademark of Oracle Corporation. It’s free to use for developing small-scale applications and is known for its scalability, reliability, and user-friendly nature. MySQL operates on a basic client-server model, making it easy to manage relational databases, with data organized in rows and columns across tables. It can run seamlessly on laptops or desktops, and client programs for MySQL can be developed in various programming languages, including C, C++, Java, PHP, Python, Ruby, and more.
Want to explore more about MySQL? Refer to the MySQL official website.
Pros & Cons of MongoDB
- The schema of MongoDB isn’t predefined. Its dynamic schematic architecture allows it to operate with unstructured data.
- As MongoDB is schemaless, expansion plans are flexible, and extra systems and RAM can be readily added.
- MongoDB supports joins in queries, multi-Documents ACID transactions, and supports embedded & reference relationships between Documents.
- It has a very powerful and expressive query language that allows you to search, sort, and filter using any field.
- Its rich JSON-like Documents allow flexible and dynamic schemas.
- MongoDB Atlas provides a Multi-Cloud Database service on AWS, Google Cloud, and Azure for the modern Cloud era.
- It provides on-demand scaling, resource optimization tools, and real-time insights intoon your Database performance.
- It is a fault-tolerant Distributed Database with a lot of data recovery options.
- It uses a document-based query language that is nearly as strong as SQL to allow dynamic queries on documents. Check out how you can Conduct MongoDB Query Performance Analysis easily.
Pros & Cons of MySQL
- MySQL is simple and easy to use and anyone with basic SQL knowledge can work with MySQL.
- MySQL allows COMMIT and ROLLBACK for transactions.
- It has built-in support for optimizing, repairing, and checking tables.
- MySQL has a large user- community.
- MySQL is extremely versatile since it supports a wide variety of embedded applications.
- In MySQL, all passwords are encrypted and it also provides host-based authentication and is very secure.
- Its multi-threaded design with kernel threads allows you to work on multiple CPUs and implements in-memory hash tables to optimize performance.
- Supports both transactional and non-transactional storage.
Use Cases of MongoDB
MongoDB is used by companies such as IBM, Oracle, Zendesk, Sony, Intercom, and others. Here are a few of MongoDB’s most well-known use cases:
- Aadhar: Aadhar is India’s Unique Identification Project and the world’s largest biometric database. MongoDB is one of the databases it utilizes to store more than 1.2 billion people’s biometric and demographic data.
- eBay: It is a B2C and C2C eCommerce corporation that employs MongoDB for a variety of projects including search recommendations, cloud management, and metadata storage.
Applications of MySQL
MySQL has been around for nearly two decades and has provided enterprises all around the world with the simplicity of storing enormous amounts of data. Here are some of MySQL’s applications:
- Sites with a high volume of visitors, such as e-commerce or social sites.
- Sites that need stringent security standards such as government-based and compliance-heavy sectors.
Use Cases of MySQL
Airbnb, NASA, YouTube, Netflix, Pinterest, Drupal, Joomla, and other notable enterprises use MySQL. Here are a few of the most common MySQL use cases:
- Wikipedia: Wikipedia, a free web encyclopedia runs on MySQL to keep up with the rising user base. MySQL keeps the page up to date, handles content and visitors, and allows for thousands of additions and modifications.
- Twitter: T-bird is being used by Twitter to shift away from temporal sharding for tweet storage and toward a more distributed technique. T-bird is based on Gizzard, which employs MySQL.
Conclusion
We hope this MongoDB vs MySQL comparison has helped you better understand these two powerful Database Management Systems. Both MongoDB and MySQL excel in their own ways, offering distinct advantages based on your specific needs and use cases.
While MongoDB’s flexibility can save time during initial development by avoiding rigid schema definitions, MySQL’s structured schema can deliver significant performance benefits in scenarios requiring fixed data models. Ultimately, your choice depends on the demands of your project and whether a flexible or predefined schema better suits your goals.
Now that you are aware of the differences between MongoDB and MySQL and also have an understanding of why how data replication can help, can read these blogs on replicating data from both the databases:
Do let us know your thoughts about this blog and if you know any other differences in the comments.
FAQs
1. Is MongoDB better than MySQL?
MongoDB is better for handling unstructured or semi-structured data, offering flexibility and scalability for modern applications. MySQL excels with structured data, providing reliable performance for traditional relational database use cases. The choice depends on your project needs.
2. Why is SQL preferred over MongoDB?
SQL is preferred for structured data and applications requiring complex queries, ACID compliance, and strict relationships between data. It’s ideal for scenarios needing reliability, consistency, and well-defined schemas.
3. What are the disadvantages of MongoDB?
MongoDB lacks ACID compliance for multi-document transactions in earlier versions, which can affect data consistency. It also uses more storage due to its flexible schema design and may underperform complex queries compared to relational databases like MySQL.
4. Can MySQL replace MongoDB?
MySQL can replace MongoDB for applications with structured data, strict schemas, and complex queries. However, it’s less suited for handling unstructured or semi-structured data, where MongoDB’s flexible schema and scalability excel.
Easha is a programming enthusiast with 2+ years of experience. She has worked in automation test script creation, regression testing, and integration projects like Thyrocare Integration. She has a bachelor's degree in Computer Science and loves writing technical articles about data engineering. Her goal is to help people solve everyday problems through her work.
