Table of Contents
Introduction
The two most common databases for enterprise applications are MySQL and MongoDB. Even though both databases are free and open-source, they have significant variances. Based on several characteristics, we’ll compare the differences between MySQL and MongoDB database systems.
What is Mongo DB
MongoDB is a document-oriented, open-source, cross-platform NoSQL database that offers excellent performance, large data storage, a sophisticated query language, and automated scaling. It’s written in C++, developed and maintained by 10gen. The developers find it straightforward to use and learn. It uses a JSON-like format to store data. MongoDB was created with the concept of collection and document in mind.
What is MySQL
MySQL is a well-known database management system used to handle relational databases. Oracle Corporation provides support for this open-source database. Compared to Microsoft SQL Server and Oracle Database, it is a quick, scalable, and simple database management system. It’s frequently used with PHP scripts to build robust and dynamic server-side or web-based enterprise applications.
MySQL AB, a Swedish company, developed and maintains it, and it is written in the C and C++ computer languages. Many small and large businesses utilize MySQL. MySQL supports a wide range of operating systems, including Windows, Linux, macOS, and others, using the C, C++, and Java programming languages.
Difference between Mongo DB vs MySQL
| MySQL | Mongo DB |
| C and C++ are the programming languages used to create it. | It’s written in C++, Java, and C. |
| MySQL keeps track of each record in a table, which may be accessed via SQL queries. | MongoDB saves each record as a JSON-like document with a variety of structures. |
| MySQL processes and accesses the database using Structured Query Language. We are unable to alter its structure. Only inputs with a predefined schema are allowed. Unstructured and semi-structured data are not supported by MySQL. | MongoDB is a NoSQL (non-relational) database system. It means we can define and stick to the incoming data’s specified structure. Working with unstructured and semi-structured data is possible with NoSQL, which is not possible with RDBMS. Its structure can be altered. |
| Table, Row, Columns Joins are used. | It makes use of Collection, Document Field, Embedded Document, as well as links. |
| Vertically, it scales in. | Horizontally, it scales in. |
| It is not possible to cancel the query while it is running. | This database system enables us to halt the query in the middle of its execution. |
| Its user interface is MySQL Workbench. | Its user interface is SQL Server Management Studio (SSMS). |
| On May 23, 1995, it was initially released. | On April 24, 1989, it was first released. |
| You’ll need a username, password, and host to access the database. | You’ll need a login, password, and profile validation to access the database. |
| It can only be used with a static system. | It can deal with both static and dynamic systems. |
| The schema design cannot be altered once it has been defined. | It supports dynamic schema since its schema design can be updated. |
| If the index isn’t found, the database engine looks for rows across the entire table. | If the index isn’t found, the database engine scans every document in the collection for exact matches. |
| 8.0.21 MySQL (February 2020) | 4.2 MongoDB (February 2020) |
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