MongoDB and MySQL are two well-known and widely used databases. While MySQL is a relational or SQL database, MongoDB is a NoSQL or non-relational database . MongoDB is particularly used to store unstructured data, whereas MySQL has its application in developing web applications, and both these databases are open-source.
This article will walk you through the differences between MongoDB and MySQL databases. To begin with, we shall discuss MongoDB and MySQL databases with their pros and cons.
So, let us get started!
What is MongoDB?
MongoDB is a document-oriented, cross-platform NoSQL database. Licensed under the Server Side Public License, MongoDB is developed by MongoDB Inc. It is an ideal choice for storing vast amounts of distributed data. It is compatible with Windows Vista and later, OS X 10.7 and higher, Linux, Solaris, and FreeBSD systems.
In addition, MongoDB offers official driver support for major programming languages, including Python, PHP, JavaScript, Ruby, Perl, Java, Go, Scala, and Swift. It does not use tables like relational databases; instead, it consists of collections and documents to store data.
A collection is a set of documents, and documents are in the BSON format, i.e., a binary representation of JSON documents. While collections are similar to rows, documents are similar to columns in relational databases .
The data in documents is stored in the form of key-value pairs, called fields. The field values can be any of the BSON data types, like string, boolean, double, etc. In addition, MongoDB supports nested or embedded documents, i.e., a document inside another document.
Pros of MongoDB
- There is no need to design a database’s schema as it is a schemaless NoSQL database.
- With the majority of data being stored in RAM, MongoDB accelerates the execution of queries.
- MongoDB supports sharding, i.e., it splits data into small chunks and stores them on multiple MongoDB instances. Therefore, MongoDB offers horizontal scalability.
- It can seamlessly integrate with Hadoop.
- Queries in MongoDB are easier to understand and learn than SQL queries.
- It creates multiple copies of data and distributes these copies to various servers. Hence, even if one server fails, the data can be accessed from another server.
Cons of MongoDB
- As MongoDB stores most of the data in RAM, it requires more memory.
- The maximum BSON document size in MongoDB is 16 MB.
- It does not allow the nesting of documents for more than 100 levels.
What is MySQL?
MySQL is an open-source SQL or relational database management system (RDBMS). Micheal Widenius is the co-founder of MySQL, and he named this database management system by combining his daughter’s name ‘My’ with the acronym of Structured Query Language, ‘SQL.’ MySQL is owned and maintained by Oracle Corporation.
Licensed under the GNU General Public License, it is a cross-platform RDBMS compatible with Linux, FreeBSD, macOS, Windows, and Solaris. MySQL stores data in the form of tables, i.e., rows and columns, and uses the Structured Query Language (SQL) to access and retrieve the stored data.
Unlike MongoDB, MySQL requires users to define a specific database schema depending upon the requirements. The schema also needs to mention rules that define the relations among various fields of a table.
Pros of MySQL
- Data security is one of the most desirable benefits of MySQL.
- It is a go-to solution for data integrity as it follows the ACID properties, unrestricted low-level locking, and multi-version transaction.
- MySQL offers various built-in tools for spatial analysis and query analysis.
- It supports trigger-based and log-based replication SSL.
Cons of MySQL
- Transactions associated with the system catalog do not follow the ACID properties.
- MySQL versions less than 5.0 do not support stored procedures, COMMIT, and ROLE.
- It does not handle large data sets efficiently.
- Poor performance scaling.
MongoDB vs MySQL
Following are the key differences between MySQL and MongoDB databases:
| MySQL | MongoDB |
| It stores data in the form of tables. | It stores data in the form of collections and documents. |
| You need to define the schema of a database in MySQL before inserting data. | MongoDB is a schema-less database, i.e., it does not require you to define the structure of documents. |
| As MySQL uses rigid tables, developing applications using MySQL is relatively slower. | Data in MongoDB is stored in the form of JSON documents, which accelerates the application development process by 4 to 5 times. |
| Data in MySQL is stored across multiple tables. Hence, we need to access multiple tables to read or write data. | Reading and writing data in MongoDB take place in a single document; each document contains the data required for a single entity. |
| Each data record is stored as a row in a table. | In MongoDB, each data record is stored as a document. |
| It is ideal for storing structured data. | It is a perfect choice for storing structured as well as unstructured data. |
| The Structured Query Language (SQL) is used to access and retrieve data from a database. | It uses JavaScript as a query language. |
| MySQL supports joins. | MongoDB supports nested or embedded documents. |
| You can consider using MySQL if data security is the primary factor. | You can use MongoDB if the majority of your services are cloud-based. |
MongoDB vs MySQL: Data Modeling
Data modeling is one of the biggest differences between MongoDB and MySQL. MongoDB uses a document-oriented model, where data is stored as flexible JSON-like documents inside collections. MySQL uses a relational model, where data is organized into structured tables consisting of rows and columns.
|
Data Modeling Aspect |
MongoDB |
MySQL |
|
Database Model |
NoSQL document database |
Relational database (RDBMS) |
|
Basic Data Unit |
Document |
Row |
|
Data Grouping |
Collections |
Tables |
|
Data Format |
BSON documents, conceptually similar to JSON |
Rows and columns |
|
Schema |
Flexible schema; documents in the same collection can have different fields |
Structured schema defined through tables and columns |
|
Relationships |
Usually handled through embedded documents or references |
Primarily handled using primary keys, foreign keys, and joins |
|
Normalization |
Often uses denormalized models to keep related data together |
Commonly uses normalization to reduce data duplication |
|
Nested Data |
Naturally supports nested documents and arrays |
Requires separate tables or related structures for complex nested data |
|
Schema Changes |
Generally easier to accommodate evolving document structures |
Usually requires explicit schema changes such as ALTER TABLE |
|
Best Suited For |
Applications with flexible, hierarchical, or frequently changing data |
Applications with structured and highly relational data |
MongoDB vs MySQL: Querying and Query Language
MongoDB and MySQL use different approaches to querying data. MySQL uses SQL (Structured Query Language) to work with tables and relational data, whereas MongoDB uses its MongoDB Query API to work with documents stored in collections.
|
Querying Aspect |
MongoDB |
MySQL |
|
Query Language |
MongoDB Query API |
SQL |
|
Data Structure Queried |
Documents in collections |
Rows in tables |
|
Basic Retrieval |
find() |
SELECT |
|
Filtering |
Query documents using operators such as $gt, $lt, and $in |
Use WHERE conditions |
|
Sorting |
sort() |
ORDER BY |
|
Limiting Results |
limit() |
LIMIT |
|
Aggregation |
Aggregation pipelines |
GROUP BY, aggregate functions, CTEs, window functions, and other SQL features |
|
Joins / Combining Data |
$lookup can combine data across collections |
JOIN operations combine data across tables |
|
Updates |
updateOne(), updateMany() |
UPDATE |
|
Deletion |
deleteOne(), deleteMany() |
DELETE |
|
Schema Flexibility |
Queries can work with documents that have different structures |
Queries generally operate against a defined relational schema |
|
Best For |
Document-oriented and flexible data models |
Structured data and complex relational queries |
MongoDB vs MySQL: Security
Both MongoDB and MySQL provide security mechanisms to protect databases, applications, and sensitive information. The security of either system depends heavily on proper configuration, authentication, authorization, encryption, network controls, patching, and operational practices.
|
Security Aspect |
MongoDB |
MySQL |
|
Authentication |
Supports authentication mechanisms to verify user identities |
Supports authentication mechanisms for database users |
|
Authorization |
Uses role-based access control (RBAC) |
Uses privileges and roles to control access |
|
User Permissions |
Permissions can be assigned through roles |
Privileges can be granted at different scopes |
|
Encryption in Transit |
Supports TLS/SSL connections |
Supports encrypted connections using TLS/SSL |
|
Encryption at Rest |
Encryption options are available depending on deployment and edition |
Encryption capabilities depend on configuration, storage engine, and deployment |
|
Network Security |
Can restrict network access and bind database services appropriately |
Can restrict connections using network and server configuration |
|
Auditing |
Auditing capabilities depend on deployment and edition |
Auditing capabilities depend on edition and available plugins/features |
|
Data Access |
Access is controlled through users, roles, and privileges |
Access is controlled through accounts, roles, and privileges |
|
Security Best Practice |
Disable unnecessary network exposure and enforce authentication |
Use strong authentication, least privilege, and secure connections |
|
Common Security Concern |
Misconfigured network exposure or weak authentication |
Excessive privileges, weak credentials, or insecure configurations |
MongoDB Security
MongoDB provides role-based access control, allowing administrators to assign users specific permissions based on their roles. It also supports secure network connections through TLS and provides security features for protecting data depending on the deployment configuration.
For example, an administrator can create separate database users with different levels of access instead of giving every application or user unrestricted permissions.
MySQL Security
MySQL provides a mature privilege system that allows administrators to control what users can do and where they can perform those operations. Permissions can be granted at different levels, depending on the database architecture and access requirements.
For example, an application may be permitted to read and update specific tables without receiving unnecessary administrative privileges.
Which Is More Secure?
It is not accurate to say that MongoDB or MySQL is universally more secure. Both provide authentication, authorization, encryption capabilities, and other security controls. In practice, security depends on how the database is configured and managed.
Organizations should follow security best practices such as:
- Use strong authentication.
- Apply the principle of least privilege.
- Encrypt sensitive connections.
- Restrict database network access.
- Keep database software updated.
- Monitor and audit access where appropriate.
- Avoid exposing database servers directly to the public internet.
- Regularly back up important data and test restoration procedures.
MongoDB vs MySQL: Data Relationships
MongoDB and MySQL handle relationships between data differently because they follow different data models. MySQL is designed around relational data, while MongoDB provides a document model that allows developers to embed related information or reference data stored in other documents.
|
Relationship Aspect |
MongoDB |
MySQL |
|
Relationship Model |
Embedded documents and references |
Tables connected through keys |
|
Primary Key |
Uses _id by default for documents |
Uses primary keys defined on table columns |
|
Foreign Key |
No traditional foreign key constraints |
Supports foreign keys |
|
Joins |
$lookup can combine documents from collections |
JOIN is a core SQL feature |
|
Embedding |
Common approach for closely related data |
Usually modeled using separate tables |
|
Referencing |
Documents can store identifiers that reference other documents |
Foreign keys reference rows in related tables |
|
Referential Integrity |
Generally handled through application logic and data modeling |
Can be enforced through relational constraints |
|
Nested Data |
Supports nested documents and arrays directly |
Usually requires additional tables or columns |
|
Best For |
Data that is naturally hierarchical or frequently accessed together |
Highly structured data with complex relationships |
Data Relationships: Which Is Better?
|
Requirement |
Better Fit |
|
Complex relationships between multiple entities |
MySQL |
|
Frequent use of joins |
MySQL |
|
Strong referential integrity requirements |
MySQL |
|
Hierarchical or nested data |
MongoDB |
|
Related data frequently accessed together |
MongoDB with embedding, when appropriate |
|
Flexible document structures |
MongoDB |
|
Highly normalized relational data |
MySQL |
Conclusion
MongoDB has gained a lot of popularity due to its ability to manage vast amounts of data with ease. On the other hand, MySQL serves to be the best option in terms of data security and is also well-known for its flexibility and high performance. If you need to work with unstructured data or are unable to predefine the schema, you can opt for MongoDB.
We have mentioned all the major differences between MongoDB and MySQL databases in this article. Both the databases have distinct features, and choosing one over the other entirely depends on your project’s requirements.
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