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Are you interested in MongoDB vs PostgreSQL comparison?
Data is a fundamental component of every business process, and a database management system is an essential requirement to store this data with security and controlled accessibility.
The two common databases in use today are MongoDB and PostgreSQL. Let’s go through a detailed comparison of MongoDB vs PostgreSQL, including their key features, differences, and similarities.
MongoDB is an open-source cross-platform document-based database. It is a non-relational database which means it can be used to store and process data in different formats. It is a NoSQL (Not only SQL) and its syntax is different from the traditional relational database management systems.
MongoDB maps document data to objects in the application code. This direct mapping helps software developers to easily use and query MongoDB. A Complex data structure can be easily stored in a document-based model of MongoDB.
MongoDB is popular for its advanced cloud-based database services. It has built-in resource optimization and task automation features. With the multi-cloud feature, you can create applications that access two or more clouds at the same time.
MongoDB can be hosted on Amazon Web Services. Google Cloud Platform, and Microsoft Azure.
Key Features of MongoDB
Some prominent features of MongoDB are as follows:
MongoDB is a schema-free database. The documents’ fields can vary. There is no need to define the structure of the document. A new field entry does not affect the other documents.
This flexibility of document-based MongoDB helps database developers to collect and store data from diverse sources. It also helps to work with changing requirements that need to be reflected in the stored document data and is a norm in software applications today.
MongoDB stored data in BSON or binary JSON format. It is an important feature of MongoDB as it makes queries faster. The serialization format stores documents and skips keys that are not required in the query, making it faster.
For this reason, MongoDB is a good choice as a database for business applications that run in real-time or deal with big data regularly. BSON helps greatly in faster data visualization and business intelligence optimization.
BSON also allows a variety of data types that are not allowed with regular JSON, such as floating-point, date, etc.
The distributed architecture of MongoDB means that different components spread across multiple platforms work together in collaboration. If there is a need to scale, it can be easily done through horizontal scaling of more platforms.
Horizontal scaling gives MongoDB an unlimited amount of scalability options. This feature makes it unique compared to relational databases that scale vertically and can get quite expensive quickly with the need for multiple servers.
MongoDB is also capable of concurrent data processing as it can serve multiple requests on multiple servers simultaneously. The parallel processing of data requests dresses load on one server and ensures data consistency while maintaining application uptime.
PostgreSQL is a completely free and open-source database management system. It is a traditional object-relational database that follows the syntax and schema of SQL databases. This means PostgreSQL structures data before them like other traditional RDMS and unlike MongoDB.
PostgreSQL can manage a range of transactions at once and can manage data for a range of applications, from web apps to data warehouses.
It is written in the popular C language and offers security features, like file system protection, the ability to restrict IP access, compatibility with external packages, etc.
Key Features of PostgreSQL
Some of the main PostgreSQL features include the following:
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PostgreSQL uses its own PL or pgSQL (procedural language). It is similar to SQL (structured query language) and provides various functions for complex queries. PgSQL is used to access, manipulate, and store data in the PostgreSQL database.
PostgreSQL follows the ACID properties of atomicity, consistency, isolation, and durability. ACID principles enable PostgreSQL for storing data and running critical transactions safely.
PostgreSQL database has a monolithic architecture which means all its components are unified. This also means that a database can also be scaled as much as the machine it is running on.
Pros and Cons MongoDB vs PostgreSQL
Some advantages of using MongoDB:
- MongoDB offers a complete cloud-based development environment.
- It offers flexible document schemas.
- The querying feature is quite extensive and feature-rich.
- It has a simple installation procedure.
- It is cost-effective.
- It has wide technical and documentation support.
Some cons of MongoDB include the following:
- MongoDB highly depends on indexing. If database indexing has discrepancies, it will affect the overall performance and speed of MongoDB. Database developers have to spend time on index analysis.
- MongoDB does not support joins. If developers want to join tables, they have to do it through manual coding, which can affect the overall performance of the database.
- MongoDB also demands high memory.
- MongoDB does not fully comply with ACID properties. It supports multi-document ACID transactions, which can result in data duplication. This can make the overall data management time-consuming.
Some pros of PostgreSQL are:
- PostgreSQL is recognized for its exceptional security features. It offers perimeter and app security. Perimeter security enables database administrators to lock features at the OS level. App security allows database access control and user privileges on the basis of read-only, read/write access, etc.
- PostgreSQL is highly extensible. Users can add language, functions, data types, etc., by just creating extensions.
- ACID compliance makes PostgreSQL reliable for storage and safe for critical transactions. It allows a transaction to succeed or fail completely, compared to successful partial writes.
A few of PostgreSQL disadvantages include the following:
- Fixed database structure limits the data contents that can be added and manipulated using PostgreSQL. The complete database schema has to be defined in the beginning and has to be followed throughout as with the other relational database model.
- Although PostgreSQL has features for performance optimization, like a Just-in-time (JIT) compiler, query planner, running parallel read queries, etc., PostgreSQL gives a slower performance compared to MongoDB due to its relational database structure.
- PostgreSQL is completely open-source. Not being owned by one company it is managed by multiple communities, and some users may run into compatibility issues. It also does not provide any warranty or liability protection.
Use Cases MongoDB vs PostgreSQL
Some of the use cases of MongoDB include the following:
- MongoDB can be easily used for the personalization of user experience on applications. It can process huge amounts of data readily in real time and offer customized features like target ads, pop-up app notifications, etc.
- Users can use MongoDB for extensive content management. MongoDB offers to store any type of data content, built any type of feature, etc., to develop a feature and content-rich application.
- The capability of MongoDB to run complex queries against big data makes it a feasible option for comprehensive customer analytics.
- The easy and fast scalability of MongoDB also makes it a viable option to scale mobile applications that usually have a lot of users.
- MongoDB provides flexibility to develop new products and services through a consolidated operational data layer. It allows faster development of features using the existing data, which helps to reach the market quickly without performing complicated procedures like data fragmentation.
PostgreSQL is used for the following:
- PostgreSQL provides extensive support for JSON data and other data types, including NoSQL through external wrappers. This makes it a central repository for multiple database systems.
- PostgreSQL offers deep analytic capabilities through feature-rich SQL support. This makes it a top choice for scientific and research projects that produce big data that has to be efficiently managed and processed.
- PostgreSQL has a prominent application in manufacturing and supply chain industries. It helps to innovate and optimize processes.
- It is a part of LAPP architecture. LAPP stands for Linux, Apache, PostgreSQL, Python, PHP, and Perl. It is used to run dynamic apps and websites.
MongoDB vs PostgreSQL – What are you planning to use?
As seen in the MongoDB vs PostgreSQL comparison, both databases are largely in use and serve unique use cases.
If you want a robust access control system with SQL feature-rich support, secure transaction process, and remarkable analytical capabilities, go for PostgreSQL.
However, if you want to store and process a range of data in different formats and in real or near-real time, document databases like MongoDB will suit your business requirements better.
You can read more about SQL vs NoSQL databases in our blog here.
Moreover, you will need competent and experienced database administrators and software developers to use the database technology successfully, whichever you choose. Experienced database developers will help you go for the right database solution that meets your business needs.
If you do not find such talent in your development team, DevTeam.Space can help you via its field-expert software developers community. These software developers and managers have experience in building and deploying market-competitive software solutions for a number of businesses.
You can also partner with these developers for your next software development project. Write to us your initial project specifications, and one of our account managers will get back to you for further assistance.
FAQs on MongoDB vs PostgreSQL
More databases are best for use in their own way. If you require a modern database to process data from various sources and in various formats, then go for MongoDB. If SQL database structure suits your application needs, PostgreSQL is a better choice.
Both databases show varying performance with different benchmarks. MongoDB is faster when it comes to raw data insertion, and relational data models, like, PostgreSQL outperforms MongoDB in data warehousing and analysis.
PostgreSQL is a traditional relational database management system with a fixed schema. It uses SQL and complies with ACID transactional properties. This makes PostgreSQL database transactions more secure. MongoDB, on the other hand, is the Not Only SQL document database with a non-fixed scheme. It stores data as JSON documents using the binary JSON format. This gives MongoDB more flexibility for data storage.