MongoDB vs MySQL: Which Should You Choose?
Organizations need to have a database that allows them to store all of the data that their companies go through each day. With the technology on databases improving year on year, there are many choices for users to pick from.
Two of the most popular options today are the MongoDB database system and MySQL database system. The debate on MongoDB vs MySQL has been raging for many years now and there seems to be no end to it just yet.
To help you decide, we’ve prepared for you a short guide that highlights the main factors that differentiate the two database architectures.
What Is MongoDB?
MongoDB is an open-source document-oriented NoSQL database that people use for storing high volumes of data. Compared to the traditional relational databases that use rows and tables, this database takes advantage of documents and collections.
Its documents utilize key-value pairs, which is basically the primary form of unit it uses. Meanwhile, its collections leverage sets of documents that are the same as relational database tables.
What Is MySQL?
MySQL is also an open-source relational database server that is trademarked under the Oracle Corporation. Just like MongoDB, it is free to use and develop within minor applications.
An awesome feature of MySQL is its ability to figure out the storage approach of the user based on their tables. This allows operators to fine-tune their database architecture according to the given scenario.
Many people use MySQL because it’s among the most responsive relational databases available today. It also provides some worthwhile features such as sharding and replication for better scalability.
Comparison Between MongoDB and MySQL
Now that we’ve gone through an overview of each database, it’s time to compare MongoDB vs MySQL to help you select the right database management system for your needs.
MongoDB vs MySQL: Security
In terms of security, MongoDB is known for providing security features such as user-based access control, authentication, and SSL/TLS encryption. The security features that you’ll get with the database will depend on what pricing tier you’ve chosen.
On the other hand, MySQL provides users with standard security policies and encryption in their basic plan. For its other two packages, you can expect firewall, auditing, masking, TDE, and encryption.
Cybersecurity is a particularly important aspect all businesses should consider especially given the increased risk of cybercrime nowadays.
MongoDB vs MySQL: Performance
MongoDB offers better performance when analyzing unstructured data as compared to MySQL. This is primarily because its data storage is based on its documents feature. Additionally, the database also has slightly increased performance as it works with objects thanks to its object storage using JSON.
As for MySQL, the database management system works great when going through transactional operations. However, you might notice a dip in performance once the data volume starts to grow in size. This effect is primarily because of the standardized formatting for its tables requiring it to go through several of them when a change or fetch request is made.
MongoDB vs MySQL: Scalability
In terms of scalability, MongoDB outshines many platforms as the top database in this regard. This is because of the system’s sharding capability, which is a method in data distribution that propagates information through various machines and collections. Basically, it enables users to put out systems with increased data sets compared to other platforms.
Thanks to its improved scalability, people can use MongoDB to develop several server clusters by simply incorporating additional servers as needed. It also lets users maintain dataset replicas within sharded clusters that have increased read and write performance capabilities.
MySQL isn’t as scalable compared to the MongoDB database system. However, it does provide users with vertical scaling, which means people can take advantage of better load by raising the RAM or CPU specifications of a server. The catch here is that there will be a certain limitation to keep an eye on.
MongoDB vs MySQL: Query Language Used
As for the query language used, MongoDB takes advantage of its own rich MongoDB Query Language, or MQL. It’s capable of data aggregation, geospatial queries, text search, and CRUD (create, read, update, delete) operations.
As for MySQL, the database system uses Structured Query Language (SQL). This means that it has access to data manipulation language, data definition language, data control language, and data transaction language.
MongoDB vs MySQL: User-Friendliness
MongoDB makes for an excellent database management system for developers thanks to its simple and easy-to-understand data storage philosophy. The system lets you maintain data within collections without enforcing schema, making it a flexible choice for developers who aren’t necessarily experts in this area.
Additionally, MongoDB supports transactions that have ACID properties. This means that isolation, atomicity, consistency, and durability are all accepted by the MongoDB database system. This gives the system added flexibility when users need to develop transactional data models as needed.
Meanwhile, MySQL is more of a choice for users who already are experienced in using the conventional SQL scripting and designing solutions expected of relational databases. People who are updating or configuring existing apps that are already compatible with relational systems will also usually choose MySQL.
At the end of the day, one’s decision in the MongoDB vs MySQL debate will come down to which database management system meets their needs the most.
MongoDB offers an open-source platform that operates as a document database with no record association and unfixed data schema. This allows its users to leverage a more flexible database that provides them with increased ability to insert the data they need.
Meanwhile, MySQL is also an open-source database that is more on the relational side. This means that the information placed here is organized as tables, which allow users to associate pieces of data with others.