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MongoDB vs MySQL: A Comparative Guide on Databases

Krunal Shah

Apr 21, 2022

9 min readLast Updated Dec 05, 2022

MongoDB and MySQL are two well-known names for databases. While MongoDB is popular for being faster when it comes to handling large amounts of data, MySQL has its own set of advantages such as on-demand scalability, data security, and high performance, to name a few. MySQL is among the list of the top three databases as of 2022 and MongoDB is one of the most used databases in 2022.

Opting for the right database as per your business requirements and goals is of utmost importance for any business. There is no specific set of rules to choosing the right database for your business, but based on the exact features/solutions you have from a database, and a thorough analysis of the available databases, you need to make a choice. However, it can be quite overwhelming to make the right decision and so we have come up with a thorough guide on MongoDB vs. MySQL, advantages of MongoDB, advantages of MySQL, and all you need to know. So, let’s get started!

What Is MongoDB?

MongoDB is defined as a document model-based database with high scalability and flexibility that helps one with querying and indexing. MongoDB is widely used to build internet applications with good scalability and availability. As it comes with a very flexible schema, developers prefer it when working with Agile methodologies during the development process.

What makes it unique is, unlike the traditional databases, it doesn’t use tables, rows, and columns to store and retrieve data. Instead, it uses different types of documents for this purpose. Here the documents come with the key-value pairs. These key-value pairs act as the units of data in MongoDB.

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What Is MySQL?

MySQL is a popular relational database management system (RDBMS) that is used in diverse sectors to store, process, and access data. MySQL was originally released on 23rd May 1995 by Oracle. It is based on structural query languages and is highly sought after due to various benefits such as data security, on-demand scalability, high performance, and many more.

Some of the unique features of MySQL include its client-server architecture, high speed, and easy learning curve. Some of the top use cases of MySQL are - OLTP (Online Transaction Processing) database, LAMP (Linux, Apache, MySQL, PHP) open-source stack, and eCommerce applications, to name a few.

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Features of MongoDB

There are a lot of features that are not only unique in MongoDB but also act as the advantages of MongoDB. Let’s have a look.

Replication to Reduce Vulnerabilities

It is important to safeguard your DBMS from any type of vulnerabilities that can lead to losing data or disrupting their normal storage. And MongoDB comes with the easy solution to create multiple copies of data and store them on multiple servers through replication.

As a result, there is always a backup of the data. This helps in the easy retrieval of data in the events of disaster, server failure, or other such events.

Indexing to Improve Query Performance

The query operations such as search, delete, modify, and others are the key functions of a DBMS. The query performance of a DBMS is measured by how accurately, efficiently, and quickly a specific query functions. And indexing is what improves the query performance significantly.

MongoDB supports indexing that ensures a minimum number of disk accesses while processing any query. For instance, a search query is only performed on the indexes instead of the whole document. This improves both the search performance and speeds noticeably.

Sharding to Seamlessly Execute Complex Queries

Sharding is the process of distributing large sets of data among various data collections to speed up complex queries. As MongoDB functions on these mechanisms, it becomes easier to execute queries with high complexity. In the sharding method, each shard of the cluster operates as an independent database. As a result, MongoDB works excellently for load balancing and scaling web apps.

Ad-hoc Queries Support for Real-time Analysis

An ad-hoc query refers to a non-standard query that arises as per the current requirements. As such queries are not pre-defined or processed as per the routines, the search results are different in this case.

MongoDB not only supports ad-hoc queries but also lets them get updated in real-time by using

MQL (MongoDB Query Language). As a result, it is the best fit for the industry applications that need real-time analytics.

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Features of MySQL

There are several features of MySQL that make it stand tall from the crowd of other relational database systems. Here’s a list of the top features of MySQL.

Robust Support for Replication

MySQL is equipped with robust, in-built support for replication. It helps in copying data from the SQL servers to the replica servers to maintain the proper backups. This also helps in improving app performance, and the overall scalability through various types of synchronizations that take place.

Password Protection for Higher Security

MySQL is very reliable in terms of security. It comes with an encrypted password system. This executes strict host verification to provide an additional layer of security.

Furthermore, MySQL 8.0 has even stronger safety & security support. It includes dual password support to let the developers change or update their passwords easily with zero downtime.

Equipped With Both Performance & Online Schema

MySQL provides you with additional advantages as it has both performance schema and online schema. Performance schema plays a vital role in monitoring the internal execution during the server runtime. On the other hand, for an online schema, the modifications to the schema table are made during the runtime of the database.

Transaction Support

It is integral for any database to have proper transaction support. And MySQL is quite competitive in terms of this feature. Be it transactions compliant with ACID (Atomicity, Consistency, Isolation, and Durability), or multi-level transactions, MySQL ensures efficient execution of all while keeping the database integrity intact. It also helps with various executions such as multi-version concurrency control, foreign key implementation, and others.

GUI support

One of the unique features of MySQL is that it provides various tools and solutions to create, design, and modify GUI (Graphical User Interface). Such simple-to-use command-line tools simplify the processes for developers, and others operating on different functionalities.

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MongoDB vs MySQL: A Comparative Overview of the Features

In the following table, we have summarized the comparative features on the basis of MongoDB vs Oracle performance or MongoDB vs MySQL performance, and other factors.




Cloud, SaaS, Web Deployment



Deployment for Developers

MongoDB Inc.

Oracle Corporation




Operating System (OS)



Data Storage


Table Format (Rows & Columns)

Query Language

Volatile Memory File System











Creation & Development



Database Conversion






Performance Analysis






Relational Interface






Integrity Model



Durability for Data Storage






Referential Integrity



Secondary Indexes



Composite Keys



Full Text Search



Geospatial Indexes



Graph Support



CAP (Consistency, Availability, and Partition Tolerance)






Data Migration






Replication Mode



System Programming Language

C, C++, Java

C, C++, C#, Python, Java, NodeJS

Next, we will discuss in detail MongoDB vs MySQL on the top comparative features.

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MongoDB Vs MySQL: Comparison of Top Features

Here we are providing you with a detailed comparative study of MongoDB vs MySQL on the basis of the top features.

Schema Flexibility

For MongoDB, its schema comes with high flexibility. There are no constraints on schema designing which makes it simple to use for different use cases. As there are notable, rows, and column structures like the conventional DBMS, all you need to do is drop the required documents in the collection. Only you need to take care of updating the schema as per the requirements for data access.

MySQL is a relational DBMS based on table structure and offers less flexibility compared to MongoDB. For instance, before running a search or modifying a query, one needs to define the related rows and columns on the table. Also, the flexibility is not that much during the deployment as well as the development process, as even a simple modification requires a change of design.


MongoDB is developed and completely owned by MongoDB Inc. and is very simple to deploy. It is compatible with a broad range of platforms and operating systems such as Windows, MacOS, Linux, and others. Also, it is a great fit for diverse types of applications including SaaS, web, and cloud applications. It's easy to comprehend and has simple to develop features that make it sought-after in different use cases.

Developed and owned by Oracle Corporation, MySQL is also quite easy to deploy or install. One can install it from the source code by following a simple manual procedure. Similar to MongoDB, MySQL has cross-platform and cross-OS compatibility. And it is also a good fit for a broad range of applications - from the web to SaaS.

Query Language

No doubt that query language implementation and usage play a very vital role in any DBMS. For MongoDB, one needs to build any query on JSON. As MongoDB has a document-based structure, here you need to specify the properties of a document with which your required result needs to match. MongoDB considers each of such document properties as an implicit boolean AND. It also supports boolean OR queries provided you use a special operator to obtain it. Simply put, MongoDB uses unstructured query language, unlike most RDBMS.

MySQL is focused on the structured query language SQL. As such query languages are simple to comprehensible and highly efficient, it simplifies various operations in MySQL such as SELECT, INSERT, DELETE, and others. MySQL query languages are of two types - Data Definition Language or DDL and Data Manipulation Language or DML. DDL statements are meant to create tables, databases, sachem, and others. And DML statements are used to insert, modify, or delete any record/records.

Integrity Model

The integrity model is another important aspect of any DBMS that determines its functionality. The integrity model of any DBMS defines the type of integrity constraints for a specific DBMS. Here the integrity constraints refer to predefined sets of protocols to be applied to a DBMS structure to establish and maintain the overall integrity, consistency, and validity of the system, the data stored, and the related functionalities.

MongoDB is based on the BASE integrity model. Here BASE refers to -

B - Basic Availability

S - soft State

E - Eventual Consistency

This integrity model of MongoDB supports both semantic and atomic transactions and updates in the DBMS. While atomic transactions are more simple and more common to execute on a single document, semantic ones are more complex in nature. Also, atomic modifications are quite common in MongoDB. For instance, if you want to update two data values within a document, there can be two possible results - both are modified successfully or, no modification takes place at all. While MongoDB does not focus that much on data consistency, for MongoDB 3.6, one can have the liberty to adjust data consistency.

MySQL is famously based on the ACID model as discussed before. The integrity model of MySQL is more focused on data consistency as well as data stability. For instance, once you execute and finish a transaction the relevant data remains stable and consistent. Note that, the related data that is stored on the disk, can have multiple distinct memory locations.

Performance & Speed

MongoDB is famous for handling large quantities of complex data easily. As it doesn’t need to deal with structuring while executing various queries, it is quite fast and performs better than the other conventional database systems. No doubt that its capacity to handle unstructured data and easy load balancing makes it superior both in terms of speed and performance.

MySQL is not that fast to deal with large and complex sets of data. As it is based on structures and required to operate on the same, executing queries for complex data often takes more time. However, for small to moderate volumes of data, MySQL can meet your requirements.

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MongoDB vs MySQL is a highly discussed topic. There is no rulebook to choose between MongoDB or MySQL. But based on the above discussion and the specific set of requirements you have, you can make the right choice. Always be clear about the type, and volume of data you will need to handle. And be transparent about the complexities they may have while performing any task or executing any query. This will help you do the right assessment and opt for the right database.

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