MongoDB vs. MySQL: Which one to choose?
MySQL and MongoDB are the most in-demand and competitive database services for web applications. Both database management systems (DBMS) enable development teams and database administrators to create reports by extracting data from a site or application, but they are designed differently. While MongoDB is a document-based system, MySQL is a legacy table-structured system.
What is MySQL?
MySQL is a popular, free-to-use, open-source relational database management system (RDBMS) developed by Oracle. SQL stands for "structured query language."
The MySQL database, created in 1995, has become a default database structure and has been widely adopted. Structured query language has been the mainstay design model for developing relational database management systems (RDBMS) to maintain data and data storage.
The language is constructed to quickly enter, categorize, search, and retrieve any data type. From a big data corporate database to small websites for local businesses, MySQL enables a standardized database design for data query, storage, and data security.
Owned by the Oracle corporation, Swedish developers created the ubiquitous database and continue to impact the database space. The relational language has been subsequently adapted by competitors, as seen with the MS SQL database server and PostgreSQL.
When applications or users need to obtain data from a MySQL database, an SQL query that joins multiple tables must be employed to create the view of the required data.
Database schemas and data models must be predefined, and data must match this schema and model to be stored in the database.
This rigid approach to keeping data offers safety in exchange for flexibility. Schema migration must occur if a new type or data format needs to be stored in the database, which can become complex and expensive as the database grows.
What is MongoDB?
Established in 2007, MongoDB Inc. was a new direction in database design, creating a way to store the enormous amount of data necessary for scalable use cases.
With the expansion of digital services and sites, the massive amount of data needed to scale this expansion presented a demand for more relaxed database management and functionality.
MongoDB's design answers a need for elegant, information-rich database implementation. It stores data as MongoDB documents, the cornerstone of its design.
Businesses employ the MongoDB database as a high-performance solution to quickly update data in structure and information.
MongoDB's design fundamentals differ from traditional relational systems. Often referred to as a non-relational (or NoSQL) system, MongoDB adopts a notably different strategy for storing data.
Contrary to relational systems' table and row format, MongoDB represents information as a series of binary JSON-like documents.
These documents consist of a series of key/value pairs of variable sorts, including arrays and nested documents.
The primary difference with traditional tables and rows is that the structure of these pairs in a specific collection can differ from document to document.
This more flexible approach is feasible because documents are self-describing.
MongoDB vs. MySQL: Similarities and differences
Similarities
These two systems share many characteristics; database management systems serve as the ground-level information network for many digital sites by storing data on a computer system or network.
Web applications require a data foundation as database services to run successfully. MongoDB and MySQL enable businesses to distribute, modify or deploy cloud-native applications.
Both systems were created as open-source databases, with code free for anyone to use and distribute.
Differences
MongoDB, also called an object-based system, is a document-based non-relational database management system designed to substitute the MySQL design as an easier way to work with data.
MySQL is an open-source relational database table-based system employing a data query structure for obtaining data. MySQL is considered an SQL database as data is searchable and accessible in relation to other data structures.
As data management and volume requirements grew, businesses began perceiving MySQL as a more rigid architecture and less flexible for reformatting data structures.
MySQL is a legacy system
MySQL has two main components; a storage engine where data is created, retrieved, sent, and stored, and the language used to access and work with data.
MySQL is also node-based, so data search is quickened by the tree design, creating an efficient search, index, and query experience. MySQL utilizes this layout to store data in fields, or data sets, that are relational to other data.
Also, you can run MySQL on virtually any operating system, though users state that Linux is optimal.
MongoDB is a NoSQL system
MongoDB, also known as a NoSQL database or non-relational system, is based upon documents as the data unit for search, making it an object-based system. It uses MongoDB query language, which many users view as a universal and more flexible structure with which to work.
Additionally, MongoDB employs BSON — JSON-like documents that are binary-coded into usually smaller files. Numerous developers find these more straightforward to manipulate, making data management quicker.
MongoDB supports various storage engine types and is developed with a dynamic "schema" design, which is how information is ordered, making it flexible and fast.
MongoDB is a valuable system for structured and unstructured data; rich media or facial recognition are just a few types MongoDB seeks to manipulate better as this type becomes even more predominant in big data.
Benefits of MySQL
MySQL is enterprise-grade and powerful across platforms and networks. It is a leader in the space and continues to create and release comparable database options, such as an upgraded blend of NoSQL DBM capabilities.
It is also known to be compatible with more systems because of its time on the market and mobility. Therefore, it is also viewed as a scalable solution.
Because of its cross-section of API, server, programmatic and administrative tools, and options, MySQL is considered highly accessible and typically runs with no downtime.
Finally, it is created with data authentication, with secure socket layer (SSL) security. The security layer makes sensitive data more protected in transmission.
Benefits of MongoDB
MongoDB's dynamic schema design fosters a more flexible environment for data search, coding, integration, and database development.
It also features easy-to-change fields, which enables users to avoid large-scale overhauls or re-calibration for changing organizational or data needs.
The document data model also provides businesses with a more sophisticated experience in storing, accessing, indexing, and combining any data for both code-friendly and native data models. Thus, conversion mapping is optional for greater durability and easier scaling.
When to use MongoDB vs. MySQL
The significant core differences between both systems mean choosing which one to use is a question of approach rather than a technical decision.
While MySQL is a time-proven relational database system offering a familiar database environment, MongoDB is a well-established, non-relational database system boasting enhanced flexibility and scalability at the cost of some safety features.
MongoDB vs. MySQL user-friendliness
MongoDB is an appealing choice for developers, as its data storage philosophy is straightforward and instantly understandable to anybody with programming knowledge.
MongoDB stores data in collections with no implemented schema, this relaxed approach to holding data makes it especially appropriate for developers who still need to be database experts to employ a database on their application.
Compared to MySQL, this flexibility is a considerable benefit: to get the best out of a relational database, you must first comprehend the principles of relational database design, normalization, and referential integrity.
MySQL is a common choice for users with comprehensive knowledge utilizing conventional SQL scripting, developing solutions for relational databases, or modifying existing applications.
Relational databases are also a more suitable alternative for applications requiring complex but strict data structures and database schemas across numerous tables.
MongoDB vs. MySQL scalability
A vital benefit of the MongoDB design is that the database is straightforward to scale. Configuring a cluster allows a portion of the database, called a shard, to be configured as a replica set that holds the same data, ensuring high availability and disaster recovery.
In a shared cluster, data is distributed across many servers. This highly flexible approach allows MongoDB to scale both read and write performance horizontally to cater to applications of any scale.
Options for scalability are much more limited with a MySQL database system: vertical scalability or adding read replicas.
Vertical scaling implicates adding more resources to the current database server, but this has an intrinsic upper limitation.
MongoDB vs. MySQL performance
Assessing the performance of two utterly distinct database systems is very challenging since both management systems approach the task of data storage and retrieval in completely different ways.
While directly comparing two SQL databases with standard SQL criteria is possible, doing the same with non-relational and relational databases is much more complex and subjective.
Analyzing the high-level query behaviors of the two designs, we can see that while MySQL is faster at selecting many records, MongoDB is significantly quicker at inserting or updating many records.
MongoDB vs. MySQL flexibility
Building and enhancing applications over time, without the need to run complex and expensive schema migration processes, is made possible by the schema-less design of MongoDB documents.
With MongoDB, there are more dynamic alternatives for revising the schema of a collection, such as building new fields based on an aggregation pipeline or reworking nested array fields.
This benefit is substantial as databases increase in size. More expansive MySQL databases are slower to migrate schemas and stored procedures. MongoDB's adaptable design makes this much less of a problem.
MongoDB and MySQL databases have a lot in common; both are free to start with, are easy to install on Linux and Windows, and have comprehensive programming language support for popular languages like Java, node.js, and Python.
MongoDB vs. MySQL security
MongoDB leverages the popular role-based access control model with a flexible permission set. Users are assigned a role granting them specific permissions over datasets and database operations.
All communication is encrypted with TLS, and it's possible to write encrypted documents to MongoDB data collections using a master key that is never available to MongoDB, achieving data encryption at rest.
MySQL supports the same encryption features as MongoDB; its authentication model is similar. Users can be granted roles but also privileges, giving them permissions over particular database operations and against specific datasets.
Conclusion
This article discusses the main differences between MongoDB and MySQL, schemaless non-relational and relational database systems.
We have explained when it is better to use one over the other while discussing each design's scalability, performance, and user-friendliness.
Finally, we have also presented both database systems' flexibility and security features from a comparison point of view.
Don't hesitate to contact us if your company needs to implement or migrate its Database Management System!