MySQL vs MongoDB: Features, Benefits and Comparison

A Database Management System (DBMS) is responsible for managing and retrieving all required information from well-organized fragments of data. MySQL and MongoDB are such databases and the most in-demand database services for web applications. Both allow you to extract data and make reports from a site or app, but they are designed differently.  MySQL is a legacy table-structured system, whereas MongoDB is a document-based system. In this article, we shall have an interesting battle of MySQL vs MongoDB, and see how both the DBMS differ.

 

MySQL vs  MongoDB: Introduction

✤ MySQL 

 

MySQL is a famous, free-to-use, and open-source Relational Database Management system (RDBMS) made by Oracle. As with other relational systems, MySQL stores data with the help of tables and rows executes referential integrity, and utilizes SQL i.e. structured query language for accessing the data.

 

When users need to recover data from a MySQL database, they must make an SQL query that merges multiple tables together to make the view of the data they require. It makes optimum usage of SQL for querying and operating database systems.

 

Database schemas and data models must be defined early, and data must correspond to this schema to be stored in the database. This strict approach to storing data presents some degree of safety but trades this for flexibility. If a new type or format of data requires to be stored in the database, schema migration should occur, which can become complex and costly as the size of the database grows.

 

✤ MongoDB

 

Similar to MySQL, MongoDB is also free to use and open source, regardless, its design principles vary from traditional relational systems. In general, it is styled as a non-relational system (NoSQL), MongoDB adopts an extremely different technique for storing data, conveying information as a series of JSON-like documents as opposed to the table and row structure of relational systems.

 

MongoDB documents include a series of key/value pairs of irregular types, including arrays and nested documents, however, the immediate difference is that the structure of the key/value pairs in a shared collection can vary from document to document. This more relaxed approach is feasible as documents are self-describing.

 

We have general information about MongoDB and MYSQL. Let’s kickstart the comparison using significant parameters.

 

MySQL vs MongoDB: Features and Benefits

✣ MySQL features 

• Support for Big  databases
• Secure and easy-to-use RDBMS
• Client and utility programs
• Allows rollback
• High-end productivity and performance
• Supports Dual password
• Partitioning

Dual Password in MySQL is the capability with syntax that saves and discards secondary passwords.

✣ MySQL Benefits

• The total cost of ownership is less
• Open-source flexibility and Data security
• Portable and Free to use
• Extensive workflow control
• On-demand scalability with the rapid development
• Stable, reliable, and powerful
• Client-Server Architecture
• Round-the-clock 24X7 uptime

✣ MongoDB features 

• Ad-Hoc Queries
• Indexing
• Aggregation
• Schema-Less Database (NoSQL)
• Scalability
• Document-oriented and open-source database

✣ MongoDB Benefits

• Installation is easy and easy to use as well
• Fully cloud-based developer platform
• Cost-effective
• Flexible
• Strong query
• Analytical capabilities
• User-friendly design
• Fast speed & high accessibility

 

MySQL vs MongoDB Comparison Table

 

Parameters  of  Comparison	MongoDB	MySQL
Brief Intro	A non-relational database system giving improved flexibility and horizontal scalability	A strong relational database system, with a common database environment for skilled IT experts
Year Released	2009	1995
Organization	MongoDB Inc.	Oracle
Performance	Follows a hierarchical data model and maintains data together, reducing the need for joins, optimized for write performance	Optimized for high-performance joins with numerous tables that are indexed, optimized for high performance across many tables
Managing Data	Large chunks of data are easy to manage	Difficult when large chunks of data are there
System Type	Non-relational or NoSQL system	Legacy system designed with SQL
Applications	Real-time analytics, content management systems, Legacy business sites, IoT, mobile apps, analytical sites, and much more	High-security sites, eCommerce sites, structured data with clear schema, social media sites, etc.
Data Representation	Shows data as JSON documents	Shows the data in tables and rows
Programming Languages Support	C, C++	C, C++, JavaScript
Supports	Inbuilt replication, sharding, and auto elections	Master slave and master replication
Schema Definition	No need to define the schema, simply drop documents	Must define tables, and columns before storing
Query Language	JavaScript as a query language	SQL as a query language
JOIN Support	Does not support JOIN operations	Supports JOIN operations
Suitable For	Projects where there is structured or unstructured data for growth	Projects where there is structured data and for a traditional RDBMS
Risks	There is no schema definition necessary so there is minimal risk of attack	Higher risk of SQL injection attack
Foreign Key	Doesn’t allow the use of foreign keys	Allows usage of foreign keys
Scalability	Is scaled horizontally and vertically	Only Scaled Vertically
Terminologies	Table, Row, Columns, Joins	Collection, Document, Field, Embedded Document
Community Support	Roughly. 213 repositories on GitHub	Around. 23 repositories on GitHub
Application Security	Uses a role-based access control (RBAC) for security	Has a privilege-based security model (PBSM)
User Friendliness	Attractive and Simple UI for developers	Managing Tables, schemas, normalization, etc is confusing at times
Architecture	Has Nexus architecture which comes with more flexibility	Contains Client-server architecture with more storage
Distributed Architecture	Yes	No
Transaction Model	Follows the BASE model with more accessibility	Follows the ACID model with more consistency
Developer Productivity	The development cycle is fast and is a developer’s delight	Development in MySQL is slow as it has strict table structures
Integration Support	Integrates well with many storage engines and uses JSON language & MongoDB query language	Uses SQL for database management & supports programming languages but is less flexible
Query Language	Uses MongoDB Query Language (MQL)	Uses SQL like any other RDBMS
Associated Indexes	In case, the index is not found, the database engine looks for documents & collection	Here, when the index is not found, the database engine looks for the whole table for the rows
Flexibility in Schema Design	Dynamic schema and design can be changed	Once defined, the schema design cannot be modified
Atomic Transactions	Multi-document transactions	Atomic transactions

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Let us expand the MongoDB vs MySQL discussion using some of the parameters of comparison for better understanding.

 

MySQL vs MongoDB: Scalability

✣ MySQL

 

Scalability in MySQL is limited. Here you have 2 choices: vertical scalability, or adding read replicas. Scaling vertically implicates adding more resources to the current database server, but this has an inherent upper limit.

 

✣ MongoDB

 

The Database is quite easy to scale. Configuring a sharded cluster lets a portion of the database, “a shard,” be configured as a replica set.

 

Replica Set is the replication of a group of MongoDB servers that contains the same data, ensuring high availability & disaster recovery.

 

MySQL vs MongoDB: Performance

✣ MySQL is optimized for high-performance joins across multiple tables that have been properly indexed. When you have to select a large number of records MySQL is fast but the data is inserted row by row.

 

✣ On the other hand, MongoDB, joins are supported with the $lookup operation, but they are less required because of the way documents tend to be utilized, they follow a hierarchical data model and retain most of the data in one document, hence eliminating the necessity for joins across multiple documents. Unlike MySQL, MongoDB is faster at inserting or updating a large number of records.

 

MySQL vs MongoDB: Flexibility

✣ MySQL 

 

MySQL databases are slower to migrate schemas and stored operations that can be dependent on the updated schemas. However, they do support embedded applications which makes them flexible.

 

✣ MongoDB

 

The schemaless design of MongoDB documents makes it very easy to build and improve applications over time, without requiring you to run complex and costly schema migration methods as you would with a relational database. In addition, there are more dynamic alternatives for updating the schema of a collection, such as creating new fields based on an aggregation pipeline or updating nested array fields.

 

MySQL vs MongoDB: Security

✣ MySQL

 

MySQL contains a strong data security layer in place to keep sensitive data safe from hackers and encrypts passwords. But, it is granted roles but also benefits, providing them permissions over certain database operations and against particular datasets.

 

✣ MongoDB 

 

It leverages the widespread role-based access control model with a flexible set of approvals. Users are assigned to a role, and that role gives them specific permissions over datasets and database operations. All transmission is encrypted with TLS, and it’s feasible to write encrypted documents to MongoDB data collections through a master key that is never known to MongoDB, achieving encryption of data at rest.

 

No doubt there are some significant differences between these two DBMS giants but, you can sense they are similar in many ways. So, before we conclude the comparison let’s have a quick look at the similarities between them.

MongoDB and MySQL: Similarities

• Both are Database Management Systems
• Both Provide Data extraction
• Have open-source and free-to-use code
• Utilize a robust query language
• Report generation
• Similar Authentication Model
• Support for Java, Python, NodeJS, PHP
• Support to deliver, modify, or deploy cloud-native apps
• Deliver full-text search and indexing search via phrase and term search
• Provide data replication
• Storage of data on the Network or a computer system

Concluding Remarks on MySQL vs MongoDB 

MySQL and MongoDB both are DBMS and capable of handling your database queries and requirements. However, MongoDB does present some better features, especially security, but, that doesn’t imply you cannot use MySQL. In fact, the Hybrid Development approach is preferred by many developers to leverage the features of both systems.

 

FAQs

 

✣ What big companies use MongoDB?

 

Companies like Forbes, Sanom, Intuit, Toyota, Verizon, Marsello, Conrad, TIM, eBay, etc. use MongoDB.

 

✣ Which companies use MySQL? 

 

Sony, BBC, Bank of America, NASA,  YouTube, Spotify, Bayer, GitHub, Airbnb, etc. are some well-known companies that use MySQL.