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Difference Between MongoDB and SQL Database


MySQL is the most inexpensive option for organizations today who are interested in utilizing relational databases these days. However, with an increase in variety or volume of data in recent years, non-relational databases like MongoDB has given new wings to the varied needs of fluid data.

MySQL was launched in 1995 and is used by the largest IT industries that include Pinterest, Twitter, YouTube, Netflix, Spotify, US Navy, NASA, Walmart, and PayPal. At the same time, MongoDB was introduced in 2009 and used by popular industries that include Citrix, Twitter, T-Mobile, Zendesk, Sony, Hootsuite, SurveyMonkey, MuleSoft, Foursquare, and InVision.

MongoDB vs MySQL: Introduction

Relational databases have been the foundation of enterprises since decades but organizations need more robust options to store or manage their data today. Also, they need robust database solutions to gain better customers insights, to meet changing user requirements, to beat competitors in the market with innovative business models. Here is a quick overview of how customers’ expectations have changed over time.

  • They need more productive business solutions with faster time to market. It results in the development of agile methodologies, microservices, DevOps, and more advanced technologies.
  • They need to manage a massive increase in structured or semi-structured data generated by new classes of the web, social, and IoT apps.
  • They need a distributed and cloud computing system that enables developers to exploit on-demand and highly scalable storage infrastructure with the ability to serve audiences around the globe while meeting a whole new set of regulatory demands for data sovereignty.

As a result, non-tabular or non-relational databases like MongoDB have emerged to address the changing needs of the new application and modernize existing workloads too. Also, MongoDB makes it easy to understand use-cases that will be used in the future as well. In this blog, we will discuss both databases in details and the major differences between the two. With this discussion, you can quickly decide on the right fit for your business.

What is MySQL?

MySQL is a popular open-source relational database management system or RDBMS that is supported, developed, or distributed by the Oracle Corporations. Like any other relational database system, MySQL stores data in tables and uses SQL (Structured Query Language) to access the data from the database.

In MySQL, you have to pre-define the database schema based on your requirements and set up rules to govern relationships among different fields in the table. If you want to change the database schema then it will start a migration process that may take the database offline for a certain timeframe and reduces application performance significantly.

What is MongoDB?

MongoDB is a non-relational, open-source database developed by MongoDB Inc. It stores the data in a binary format called the Binary JSON or BSON. The related data is stored together for faster query access with the MongoDB query language. Fields may vary from document to document and it is not required to declare the structure of documents to the system that are self-describing. In case, a new field is added to the document then it can be created quickly without affecting any other document in the collection. The best part is that it will not make the system offline like MySQL database. Optionally, schema validation is made to enforce the data governance controls over every collection.

For Example, in a table, there are columns for name and address but you want to add a new column here with the name age then how to do it. MySQL will not take the data because the column is not defined in the schema. At the same time, a new field can be added for the column in MongoDB irrespective of the schema because of dynamic schema facility.

Also, data can be mapped naturally to objects in the application mode, making it easy to learn or use by developers. Also, documents give you the ability to represent hierarchical relationships to store arrays and more complex structures quickly. Also, idiomatic drivers are offered in more than 10 languages and rich indexing to provide programmatic ways to access or analyze data of any structure.

Documents helps to bring together the related data that can be modelled together across parent-child tables in a relational schema. This database system helps to meet the data integrity needs of the majority of applications. One or more fields can be written in a single operation that includes insertion, updates etc. If any error is made, the operation can be rolled back so that clients receive a consistent view of the document.

MongoDB database system offers support for multi-document transactions, making it easy to combine speed, flexibility, and the power of document model with the intelligent distributed system design to scale-out or fix the data where it is needed. With a consistent view of data, it is easy to maintain data integrity with the highest regulatory standards. Transactions in MongoDB are highly similar to transactions made in MySQL database system. They have similar syntax and easy for anyone to add to any application.

Unlike MySQL database system, MongoDB is built on a distributed architecture. It offers out-of-the-box data localization and replica sets to maintain data availability.

MongoDB vs MySQL: What are the major differences?

Comparison Parameters MongoDB MySQL
Overview It is an open-source, non-relation database system developed by MongoDB Inc. in 2009. It is a popular open-source, relational database system developed, distributed, and supported by the Oracle Corporation.
Data Storage In MongoDB, each individual record is stored as “document”. In MySQL, each individual record is stored as a “row” within a table.
Hierarchical Relationship Documents belonging to a particular class or group are stored as the collection. A table is used to stored rows of similar types.
SQL or No SQL MongoDB is a No SQL database. It means there is no predefined structure for the incoming data with a dynamic schema facility. MySQL uses SQL or Structured Query Language for data access. We cannot change the schema for incoming data.
Data Representation MongoDB stores data in JSON-like documents. MySQL stores data in the row format within a table.
Salient Features MongoDB was designed with scalability and high availability in mind and it includes out-of-box sharding and replication features too. MySQL does not support sharding and replication features but it allows the data access using joins that minimizes duplication.

Here are a few more features comparison for your reference –

Features MySQL MongoDB
Rich Data Model No Yes
Dynamic Schema No Yes
Typed Data Yes Yes
Data Locality No Yes
Field Updates Yes Yes
Easy for Programmers No Yes
Complex Transactions Yes No
Auditing Yes Yes
Auto-sharding No Yes

Why use MongoDB instead of MySQL?

Organizations of all sizes adopt MongoDB because it enables them to build more powerful apps faster, with diverse data types, and manage apps more efficiently at a scale. Development is simplified in the case MongoDB database system as documents are mapped naturally to object-oriented or modern programming languages.

With MongoDB, you may remove the complex object-oriented (ORM) layer that translates objects in code to relational tables. The flexible data model of the MongoDB database system signifies that database schema can be modified with changing business requirements.

MongoDB can be scaled across multiple distributed data centers, offering new levels of scalability and availability that were not possible to achieve with relational databases like MySQL. As the application deployment grows in terms of data volumes and throughput, MongoDB scales quickly with the downtime and without changing your application. In contrast, scaling with MySQL always demands significant and custom engineering work.

While working with MongoDB, data is stored as flexible JSON documents, instead of rigid rows or columns within a table. Documents help to move faster and the deployment time can be optimized up to five times when compared to relational databases. A few features of JSON documents in MongoDB include:

  • Documents are natural as data is represented in the same format as applications do.
  • Documents are flexible where fields can be added anytime when required.
  • Documents make the application faster because application code is stored at a single place instead of multiple relational tables.

When use MySQL for your business?

While many organizations have successfully migrated from RDBMS system to MongoDB database as a replacement of legacy apps built around the relational model and SQL. However, organizations are also getting benefits from modernizing mission – critical, revenue generating apps to MongoDB.  As a result, it will improve customer experiences by reducing downtime during system updates.

Also, it can tap into business agility enabled by cloud computing. In this way, the decision is completely yours how to play among two popular database system and pick any one of them based on your convenience. You can club both databases together as well if required.

The Overall Verdict

Now, you are sure when to use MySQL or MongoDB database system based on your changing business needs. Today, relational databases are pushed beyond their limits because of the way how apps are built or run today and coupled with growth in data sources and user loads. To address these issues, the best idea is migrating MySQL to a MongoDB database system. To learn more on MySQL and how to migrate it to more powerful database systems.


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