MongoDB and Postgres are both great database management systems, so to select one of them it’s up to what your need is. In this article we will study the personality of each database and the type of use cases that one serves best.
Firstly, taking a brief overview about them:
MongoDB is a schema-free document database offering both free and paid plans. As a document database, MongoDB has a different structure and syntax than the traditional RDMS (Relational Database Management System). It is a NoSQL (Not Only SQL) database.
PostgreSQL is a 100% free and open-source ORD (object-relational database). Instead of storing data like documents, the database stores it as structured objects. It follows a traditional syntax and schema for SQL databases.
Secondly, let’s find out their wonderful features:
MongoDB: it is a NoSQL database so it is friendly to the user, and easy to learn. This schema processes data as JSON- type documents, which allows users to process large volumes of data faster than many other solutions, and gives the database a higher level of flexibility.
It uses BSON (Binary JSON). BSON allows for certain data types that are not used with regular JSON, such as long, floating-point, and date. The database features a distributed architecture. It means that components function across multiple platforms in collaboration with one another, and as it can be scaled across more than one platform as needed, MongoDB has nearly unlimited scalability.
MongoDB was programmed in C, C++ and JS. It offers client-side, field-level encryption through TLS AND SSL (Transport Layer Security and Secure Sockets Layer). TLS and SSL are both internet encryption protocols that make HTTP (Hypertext Transfer Protocol) turn into HTTPS (Hypertext Transfer Protocol Secure). In fact, TLS is simply an upgraded SSL of sorts, created to reduce security vulnerabilities. Users can thereby encrypt all MongoDB network traffic. Moreover, it has various safeguards to ensure the proper authentication of user identities.
MongoDB has very fast task fulfillment, in particular thanks to the fact that the data is only semi-structured. According to various reviews, it is one of the faster solutions on the market, even when dealing with huge volumes of data on a regular basis. This makes it ideal for situations where data needs to be real-time or near real-time, thereby enabling companies to get a holistic view of their business in the moment.
PostgreSQL has a monolithic architecture, which means that the components are completely united, and the database can only scale as much as the machine running it. It was programmed in C. The code is open-source and accessible to developers.
PostgreSQL offers community support and only offers additional paid support options through certain other companies.
PostgreSQL includes basic file protection, the ability to restrict client connections by IP address, and compatibility with various other external packages intended to make it even more secure.
- MongoDB has the potential for ACID compliance, while PostgreSQL has ACID compliance built-in. ACID (atomicity, consistency, isolation, durability) are principles or components that work towards data validity, especially in databases intended for transactional workflows.
- MongoDB uses collections for the same purpose that PostgreSQL uses tables. These collections include options for setting validation rules and setting maximum sizes. PostgreSQL describes tables in a very specific language and structures the data in such a way that the database or an ELT tool can process it.
- MongoDB uses documents to obtain data while PostgreSQL uses rows for the same purpose.
- While MongoDB does not support FOREIGN KEY constraints, PostgreSQL does.
- MongoDB uses redundant replica sets, and PostgreSQL performs synchronous or 2-safe replication to maintain data sets.
- SQL databases like PostgreSQL use joins to combine data from multiple tables into a single table. MongoDB uses indexes, which are only one component of a join.
Finally, Tips to select one of them:
Common use cases for MongoDB include customer analytics, content management, business transactions, and product data. The database is also ideal for mobile solutions that need to be scaled to millions of users, thanks to its ability to scale.
Use cases for PostgreSQL include bank systems, risk assessment, multi-app data repository, BI (business intelligence), manufacturing, and powering various business applications. It is ideal for transactional workflows. Also, PostgreSQL has fail-safes and redundancies that make its storage particularly reliable. This means that it is perfect for important industries like healthcare and manufacturing.
As we have mentioned before, to pick which one’s suitable to your project, it’s depended on your purposes:
- If you are at the beginning of a development project and are seeking to figure out your needs and data model by using an agile development process, MongoDB will shine because developers can reshape the data on their own, when they need to.
- If you are supporting an application you know will have to scale in terms of volume of traffic or size of data (or both) and that needs to be distributed across regions for data locality or data sovereignty, MongoDB’s scale-out architecture will meet those needs automatically.
- If you want a multi-cloud database that works the same way in every public cloud, can store customer data in specific geographic regions, and support the latest serverless and mobile development paradigms, MongoDB Atlas is the right choice.
- If you are a SQL shop and introducing a new paradigm will cost more than any other benefits mentioned will offset, PostgreSQL is a choice that will likely meet all your needs.
- If you want a relational database that will run complex SQL queries and work with lots of existing applications based on a tabular, relational data model, PostgreSQL will do the job.