Introduction To MongoDB
Introduction to MySQL
MySQL is an Open-Source, Multithreaded, Multi-user, Relational Database Management System developed and supported by Oracle. MySQL is available for free for building small-scale applications. MySQL is fast, scalable, reliable, and easy to use. Each Database in MySQL consists of a collection of tables. Client Applications for MySQL can be written in C, C++, Eiffel, Java, Perl, PHP, Python, Ruby, and Tcl.
Difference between MongoDB and MySQL
- Data Structure
In MySQL, records are stored in the form of a table with rows and columns. Each individual record represents a row in the table and different attributes represent columns of a table.
- SQL or NoSQL
MongoDB is a Document-oriented Non-relational or NoSQL Database. Unlike the relational database, there are no tables, rows, primary keys, or foreign keys. Instead, the incoming data can be defined and conformed to different structures. Even different documents in a collection can have different structures if required. Hence, data stored in MongoDB has a dynamic schema.
MySQL as the name suggests is a SQL or Relational Database. Data is stored in tabular format with relationships defined. The schema can not be modified. The inputs following the given schema are only accepted.
MongoDB’s Nexus Architecture design philosophy combines the features of a Relational Database while also catering to the demands of modern-day applications through flexible schema, high scalability, and globally accessible deployment. Furthermore, a Distributed System Architecture enables users to intelligently place data wherever they want it.
MySQL follows a Client-Server Architecture with storage optimized for multi-threading and high performance. It is designed so that end-users or Clients can access the resources from Computer i.e., a server using various networking services. The Architecture of MySQL is comprised of the following key layers :
- Storage Layer
- Query Language
MongoDB uses an unstructured query language, called MongoDB Query Language (MQL), which is rich and expressive. It supports CRUD operations (Create, Read, Update, Delete), Data Aggregation, Text Search, and Geospatial queries.
MySQL uses Structured Query Language (SQL) like any other Relational Database. SQL has Data Definition Language (CREATE, ALTER, and DROP tables), Data Manipulation Language (INSERT, UPDATE and DELETE rows), Data Transaction Language (COMMIT, ROLLBACK, etc), and Data Control Language (GRANT and REVOKE) to communicate with the database.
- Schema Flexibility
MongoDB has a flexible schema design that allows you to fulfill the modern-day requirements of Big Data applications. With MongoDB, you can easily store and combine any type of data and dynamically alter schema without experiencing application downtime.
MySQL is excellent if you have a predefined and fixed schema. It enables you to maintain consistency in data. In the case of a dynamic schema requirement, MySQL is challenging to implement.
MongoDB supports Sharding and Replication. Replication refers to the Technique of copying data from the primary server node to multiple secondary server nodes. Sharding is the process of managing horizontal scaling across various servers using a shared key.
MySQL supports Master-Slave Replication and Master-Master Replication. Master-Slave Replication enables data from one database server, the Master, to be copied to one or more other database servers i.e., Slaves. In Master-Master Replication, both nodes are masters and replicas at the same time, resulting in circular replication between the nodes.
As a modern non-relational Database, MongoDB is designed to be scaled efficiently through both vertical and horizontal scaling.
MySQL Database can be scaled using Vertical or Mixed (hybrid) approaches but not fully Horizontally.
- Performance & Speed
The performance of MongoDB on unstructured data is relatively quick to that of MySQL because of its Documents-based (JSON type) data storage. It can also accept larger amounts of structured or unstructured data faster than MySQL. Hence, MongoDB is optimized for Write Performance.
MySQL excels in transactional operations. But performance becomes slower when the data volume increases largely since the tables are stored in a normalized format. However, MySQL is optimized for high-performance joins across multiple tables.
For small-scale applications on the shared Cloud, MongoDB can be used free of cost on the M0 cluster. Factors that decide the pricing tier are the type of Cloud, amount of storage, security standards, etc. Cloud MongoDB Database has three pricing tiers: Serverless, Dedicated and Shared. The price estimate of the Dedicated tier is $57/ month and Serverless starts from $0.30/million reads. You can contact the sales team to get an accurate estimate for your use case for on-Cloud, on-premise, or app-based databases.
For commercial purposes, MySQL has three pricing editions each with its features and constraints:
- Standard Edition: $2000/annum
- Enterprise Edition: $5000/annum
- Cluster CGE: $10,000/annum
MongoDB’s security consists of role-based access control that includes authentication, access control, and encryption (TLS/SSL) for sensitive data. The security features are also determined by the pricing tier.
MySQL follows a privilege-based security model that requires user authentication and can grant or restrict user rights on a particular database. For the Standard Edition, MySQL provides normal encryption and security policies. However, for the other two editions, it provides authentication, TDE, encryption, masking, firewall, and auditing.
This blog talks about a few of the primary differences between MongoDB and MySQL in detail. It also gives a brief overview of the introduction of the two databases.
Mustafa Al Mahmud is the Founder and CEO of Gizmo Concept and also a professional Blogger, SEO Professional as well as Entrepreneur. He loves to travel and enjoy his free moment with family members and friends.