Choosing the Right Database – MongoDB vs PostgreSQL vs MySQL for Web Applications
The main component of any web application is its data. This data should be carefully monitored and handled to provide the necessary data to the application. We use databases to keep these records such that it becomes convenient in handling a large number of data in day-to-day operations. Here we are going to discuss how you can choose the right database among MongoDB, MySQL or PostgreSQL
Relational vs Non-Relational databases
It is important to have a clear understanding of what kind of databases are available for you to choose and what are their differences.
Relational Databases
Relational databases store data in tabular formats. This type is also called SQL databases because they use SQL for database operations. Even though NoSQL databases are becoming more popular, SQL databases are still popular for their high stability, reliability, and the ability to adhere to the standards to cope with trending software stacks.
Non-relational Databases
Non-relational databases store data in non-tabular formats like documents. We refer to them as NoSQL databases as well. Unlike relational databases, non-relational databases don’t require a clearly defined schema. Therefore, these databases are usually popular when you have to deal with large amounts of unstructured data.
What to consider when choosing a database
As for now, there are many databases with different features. Therefore picking up a suitable database will be quite challenging. There are a few main factors that you should consider when choosing a database management system
Vertical or horizontal scaling
This is very important if you have limited server resources because with vertical scaling you can add more computational power instead of having more servers in the system. This is convenient when there are fewer users and querying involved. vertical scaling gives speed and simplicity to the system. When there are higher loads, horizontal scaling can distribute the load across servers.NoSQL databases such as MongoDB will be a good choice in terms of this.
Speed
If speed is critically important over other parameters like atomicity, consistency, isolation, durability then again a non-relational database like MongoDB is a good choice, If your application deals with real-time data, such as data retrieved from sensors where data integrity depends on the speed, again non-relational database have plus points, because they record each data as an independent entity. Therefore you can run multiple queries simultaneously.
Atomicity
If your application logic is interconnected, atomicity should be a priority. That means that all the components of the flow should be successful to achieve overall success. If this is the case, your choice should be a relational database such as MySQL and PostgreSQL.
Choosing the most suitable database for your application
When should you use MongoDB?
MongoDB is a document-based open-source NoSQL (Non-Relational) database specifically designed to store and manage unstructured data. It uses BSON which is a binary JavaScript Object Notation. BSON is optimized for data retrieving and storing. With BSON, you can query fast. However, since BSON is not human readable, it is translated to JSON when viewing documents. Because of this, MongoDB is kinda popular for web applications based on Node.js. MongoDB offers high efficiency and reliability eventually resulting in a high-performance database, which will enhance your storage capacity too.
With MongoDB, you do not have to worry about deciding the structure of your database. As MongoDB does not require to have a schema, you can change the hierarchical structure of your database at any time. In addition, you can achieve high scalability and availability with Auto-sharding and on-board replication. Also with MongoDB, you don’t have to follow complex models as it is designed to operate easily.
MongoDB comes with different pricing plans to be matched by both startups and large enterprises. So that’s something you need to consider when selecting MongoDB for your application. In this guide, you can learn how to install MongoDB in AWS.
MongoDB is ideal for highly read, rarely written or highly written, rarely read kind of data. This is a good choice for blogs, logging applications and real-time data analytic web applications.
However, MongoDB is not the ideal option for you if you have data that should be stored in tabular format and want to have relationships between them. Since it targets unstructured data storage, it cannot guarantee the the security of data which can be a major drawback for your application
When should you use MySQL?
MySQL is an open-source, free, relational database management system. Even though this is supposed to be a free tool, there are paid versions with additional features. Though NoSQL databases are slowly becoming the trend, people still choose MySQL since it has been enriched for about 40 years now. The main advantage of using MySQL is that it is highly compatible with various other database systems. Therefore data migration is not an issue anymore. Apart from, that it prioritizes speed and agility over other features
MySQL offers replication support which improves app performance and scalability through synchronization. If you have fixed schemas and table structure, a high transaction rate is needed with a low maintenance cost, this can be recommended. Data security is there in MySQL as they use an encrypted password system and it is considered to be the most secured database for now. If you have an enterprise-level application that does not need scaling critically but needs high performance yet has a strict budget, MySQL is a wise choice for you. Wikipedia, Twitter,, and BBC are some of the popular use cases of MySQL.
Even with the above advantages, MySQL is not recommended if your application handles larger datasets that need to be analyzed. Even clustering won’t be an effective solution since it takes more time. Anyway, Here is a nice guide on how to install MySQL on AWS.
When should you use PostgreSQL?
PostgreSQL is also an open-source and free database. The most attractive thing about PostgreSQL is that although it’s a SQL database, it also supports NoSQL data formats. Furthermore, PostgreSQL has a catalog-driven approach which makes it highly extensible. Therefore, with PostgreSQL, you can define the functional language, data and index types in addition to the ordinary tables. You have the freedom in choosing the servers as this works on both on-site and cloud-based servers.
When there is no requirement to alter your data very frequently or if you have structured data with multiple relationships and you need to have a large number of tables linking them, you can use PostgreSQL.
PostgreSQL has multiple features such as table inheritance, support for various data types,, etc. Most importantly this is considered to be the highest rank among ACID Compliant databases. This is also a great choice if your major concern is data integrity.
PostgreSQL is not rich with documentation. Therefore you will have a hard time if you ever run into any kind of an issue in the middle because then most of the time you will have to seek help from a private PostgreSQL support team. This database works well with read-write operations but there can be a slow down in reading-only operations. This guide will teach you how to setup PostgreSQL on AWS.
Conclusion
As we went through the details we can see that every database has its own drawbacks and advantages. There is no “the best “ database for all applications. You have to select wisely after walking through your requirements carefully. As a summing up, we can say if you want to define relationships among data you can go with MySQL (You can achieve the same in PostgreSQL). If you have highly manipulatable or real-time data to manage MongoDB is indeed the best choice. PostgreSQL is a good choice if you have the direct benefits of getting JSON support. The choice is yours!
