MongoDB vs MySQL – Difference Between Them

Key Difference Between MongoDB and MySQL

• MongoDB represents data as JSON documents, whereas MySQL represents data in tables and rows.
• In MongoDB, you don’t need to define the schema, while in MySQL, you need to define your tables and columns.
• MongoDB doesn’t support join, but MySQL supports join operations.
• MongoDB uses JavaScript as a query language, while MySQL uses Structured Query Language (SQL).
• MongoDB is an ideal choice if you have unstructured and/or structured data with the potential for rapid growth, while MYSQL is a great choice if you have structured data and need a traditional relational database.
• If most of your services are cloud-based, MongoDB is best suited for you, but if data security is your priority, then MySQL is the best option for you.

Here, I have analyzed the difference between MongoDB and MySQL and will comprehensively evaluate their pros and cons.

What is MongoDB?

MongoDB is a document-oriented NoSQL database used for high-volume data storage. MongoDB is a database that came into light around the mid-2000s. It falls under the category of a NoSQL database.

This kind of DBMS uses dynamic schemas, which means that you can create records without first defining the structure, such as the fields or the types and their values.

MongoDB allows you to change the structure of records, which we call documents, by adding new fields or deleting existing ones.

Features of MongoDB

In my hands-on work with MongoDB, these are the important features:

• Each database contains collections, which in turn contain documents.
• Each document can be different, with a varying number of fields. The size and content of each document can be different from each other.
• The document structure of MongoDB is determined by how developers construct their classes and objects in their respective programming languages.
• Rows don’t need to have a schema defined. Instead, the fields can be created on the fly.
• MongoDB allows you to represent hierarchical relationships, store arrays, and other more complex structures more easily.

Why use MongoDB?

I’d like to share the key reasons why I chose MongoDB:

• MongoDB is very flexible and adaptable to real-world business situations and requirements.
• Queries can be made to return certain fields within documents.
• MongoDB supports fields, range-based queries, regular expressions, etc. for searching the stored data.
• MongoDB is a very easy DBMS system that can easily scale up or down.
• MongoDB helps you use internal memory for storing temporary working datasets, which is much faster.
• MongoDB offers primary and secondary indexes on any field.
• MongoDB supports the replication of the database.
• You can use MongoDB as a file storage system, which is known as GridFS.
• MongoDB offers various methods to perform aggregation operations on the data, like the aggregation pipeline, map-reduce, or single objective aggregation commands.
• MongoDB allows you to store any type of file, which can be any size, without affecting our stack.
• MongoDB basically uses JavaScript objects in place of the procedure.
• MongoDB supports special collection types like TTL (Time-to-Live) for data storage that will expire at a certain time.
• The dynamic database schema used in MongoDB is called JSON.
• Indexes can be created to improve the performance of searches within MongoDB. Any field in a MongoDB document can be indexed.
• Replication: MongoDB can provide high availability with replica sets.
• MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure.

Disadvantages of using MongoDB

From what I’ve observed, here are the disadvantages of using MongoDB:

• MongoDB is not strong ACID (atomic, consistency, isolation, and durability) when compared to many other RDBMS systems.
• Transactions using MongoDB are complex.
• In MongoDB, there is no provision for stored procedures or functions, so you can’t implement any business logic at the database level, which you can do in any RDBMS system.

What is MySQL?

MySQL is a popular and widely used DBMS system. The name is taken from the girl named My, who is the daughter of co-founder Michael Widenius. The source code of MYSQL is available under the GNU GPL. The project is owned and maintained by Oracle Corporation.

It is an RDBMS (Relational Database Management System) and works primarily on the relational database model. It makes database administration easier and more flexible.

In MySQL, you need to pre-define your database schema based on your requirements and set up rules that help you govern the relationships between fields in your tables.

Features of MYSQL

In my experience, here lies an important feature of MySQL.

• MySQL is a community-driven DBMS system.
• Compatible with various platforms using all major languages and middleware
• It offers support for multi-version concurrency control.
• Compliant with the ANSI SQL standard
• Allows log-based and trigger-based replication SSL
• Object-oriented and ANSI-SQL2008 compatible
• Multi-layered design with independent modules
• Fully multi-threaded, using kernel threads
• Servers are available in embedded DB or client-server models.
• Offers built-in tools for query analysis and space analysis.
• It can handle any amount of data, up to as much as 50 million rows or more.
• MySQL runs on many flavors of UNIX and Linux.

Why use MySQL?

Here are some important reasons we rely on MYSQL:

• Supports features like master-slave replication and scale-out
• It supports offload reporting, geographic data distribution, etc.
• Very low overhead with the MyISAM storage engine when used for read-only applications
• Support for a memory storage engine for frequently used tables
• Query cache for repeatedly used statements
• You can easily learn and troubleshoot MySQL from different sources like blogs, white papers, and books.

Disadvantages of using MySQL

Here, I want to present the cons and drawbacks of using MySQL, which I’ve personally faced while utilizing this database system.

• Transactions related to the system catalog are not ACID-compliant.
• Sometimes a server crash can corrupt the system catalog.
• Stored procedures are not cacheable.
• MYSQL tables, which are used for the procedure or trigger, are most pre-locked.

MongoDB vs MySQL: Know the Difference

From my extensive experience, it’s clear there are important differences between MongoDB and MySQL:

MongoDB	MYSQL
MongoDB represents data as JSON documents.	MySQL represents data in tables and rows.
In MongoDB, you don’t need to define the schema. Instead, you just drop in documents; you don’t even need to have the same fields.	MySQL requires you to define your tables and columns before you can store anything, and every row in a table must have the same columns.
MongoDB has a pre-defined structure that can be defined and adhered to, but if you need different documents in a collection, it can have different structures.	MySQL uses Structured Query Language (SQL) for database access. You can’t change the schema.
Supported languages are C++, C	Supported languages are C++, C, and JavaScript.
Ongoing development is done by MongoDB, Inc.	Constant development is done by the Oracle Corporation.
MongoDB supports built-in replication, sharding, and auto-elections.	MySQL supports master-slave replication and master replication.
If an index is not found, every document within a collection must be scanned to select the documents that match the query statement.	If an index is not defined, then the database engine needs to scan the complete table to find all relevant rows.
GPL v2/commercial license available OD	GNU AGPL v3.0/ Commercial licenses available OD
If most of your services are cloud-based, MongoDB is best suited for you.	If data security is your priority, then MYSQL is the best option for you.
MongoDB places no restrictions on schema design.	MySQL requires you to define your tables and columns before you can store anything. Every row in a table must have the same columns.
MongoDB uses JavaScript as the query language.	MySQL uses the Structured Query Language (SQL).
MongoDB doesn’t support JOIN.	MySQL supports JOIN operations.
It has the ability to handle large amounts of unstructured data.	MySQL is quite slow in comparison to MongoDB when dealing with large databases.
Real-time analytics, content management, the internet of things, mobile apps	Structured data with a clear schema
No schema definition is required, so there is less risk of attack due to the design	Risk of SQL injection attacks
This is an ideal choice if you have unstructured and/or structured data with the potential for rapid growth.	This is a great choice if you have structured data and need a traditional relational database.

How to Choose Between MongoDB and MySQL

We’ve seen firsthand how MongoDB’s document-oriented model and MySQL’s relational structure offer distinct advantages. Depending on whether you prioritize flexibility and growth or structured data integrity, one will suit your project better than the other.