MongoDB vs PostgreSQL: 9 Key Differences

Learn about the 9 key differences between MongoDB and PostgreSQL so you can choose the right database for your project.

Updated: 29 Jun, 23 by Susith Nonis 9 Min

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MongoDB and PostgreSQL are the most popular and widely used database management systems. While both are designed to store and manage data, they have some significant differences in architecture, functionality, performance, and scalability. In this article, we will explore the key differences between MongoDB and PostgreSQL to give you a better understanding of which one to choose based on your specific requirements.

MongoDB is the new kid on the block in database management systems. It is a document-oriented database, storing data as documents rather than in tables and rows like traditional relational databases. Think of it like a digital filing cabinet, where each document is unique and contains all the necessary information to access and manipulate it. The best part? No more tedious SQL queries! MongoDB uses a simple and intuitive query language that makes searching and retrieving data a breeze.

Another cool thing about MongoDB is its ability to scale horizontally. With its distributed architecture, you can easily add more nodes to your cluster as your data grows without sacrificing performance. It's like having an army of data minions working tirelessly to ensure your applications run smoothly. Plus, MongoDB is open source, which means it's free to use, and you can contribute to its development. So, if you're looking for a cutting-edge database that's easy to use and can handle any workload, MongoDB might be the perfect fit for you.

PostgreSQL is like that old, reliable friend you can always count on. It's been around since the '80s and has evolved into a robust and stable database management system. PostgreSQL is a relational database that stores data in tables and rows with relationships between them. If you're a fan of SQL, PostgreSQL is your jam. It offers a rich set of features for complex queries and supports advanced data types like arrays and JSON. 

One of the coolest things about PostgreSQL is its extensibility. You can create custom data types, functions, and even programming languages to run inside the database. It's like having a Swiss army knife for data management. Plus, PostgreSQL is open source and has a vibrant community of contributors constantly improving its performance and adding new features. Whether building a simple web app or a complex data warehouse, PostgreSQL is a solid choice that won't disappoint you.

Data Modeling

One of the key differences between MongoDB and PostgreSQL is their data modeling approach. MongoDB is a document-oriented database that stores data as JSON documents. Each document contains all the necessary information about an object, and you can nest documents within documents to represent complex data structures. On the other hand, PostgreSQL is a relational database that stores data in tables and rows. In PostgreSQL, you define a schema with a fixed set of columns and data types and have to fit your data into that schema.

The advantage of MongoDB's data modeling approach is its flexibility. A fixed schema does not limit you, and you can easily add or remove fields from your documents as your data changes. On the other hand, PostgreSQL's rigid schema provides more control over data integrity and consistency. It ensures data is stored in a standardized format and prevents missing or duplicated data.

Query Language

MongoDB uses a query language called MongoDB Query Language (MQL), which is similar to SQL but optimized for handling JSON data. MQL is a powerful and intuitive language that supports complex queries, aggregation, and full-text search. PostgreSQL, on the other hand, uses SQL, which is a standard query language used by most relational databases. SQL offers a rich set of features for querying data, including joins, subqueries, and window functions.

The advantage of MQL is that it is specifically designed for handling JSON data, which makes it easier to work with when dealing with complex data structures. However, if you are already familiar with SQL, PostgreSQL's query language should be easy to learn and use. SQL is a mature language with a large user community, so you can find plenty of resources and support online.

ACID Compliance

ACID (Atomicity, Consistency, Isolation, and Durability) is a set of properties that ensure transactions are completed successfully despite errors or system failures. MongoDB and PostgreSQL are ACID compliant but achieve it in slightly different ways. MongoDB uses multi-document transactions, which allows you to perform transactions on multiple documents in a single operation. PostgreSQL, on the other hand, supports traditional SQL transactions, which are more familiar to developers.

The advantage of MongoDB's multi-document transactions is that it allows you to perform complex operations on multiple documents with a single transaction. However, PostgreSQL's traditional SQL transactions are more widely understood and supported, making it a safer choice for mission-critical applications.


Scalability refers to a database's ability to handle increasing data and users without sacrificing performance. Both MongoDB and PostgreSQL are scalable but achieve it in different ways. MongoDB scales horizontally by sharding data across multiple nodes, which allows it to handle large amounts of data and traffic. PostgreSQL scales vertically by adding more resources to a single instance, such as CPU, memory, and storage.

The advantage of MongoDB's horizontal scaling is that it can handle unlimited data and traffic by adding more nodes to the cluster. On the other hand, PostgreSQL's vertical scaling is more limited by the resources available on a single instance. Still, it is easier to manage and maintain than a cluster of nodes.

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Replication is copying data from one database to another to ensure high availability and redundancy. Both MongoDB and PostgreSQL support replication, but they do it in slightly different ways. MongoDB uses replica sets consisting of multiple nodes that synchronize data. PostgreSQL uses streaming replication, which involves real-time data copying from one server to another.

The advantage of MongoDB's replica sets is that they provide automatic failover and data redundancy, which makes it easier to ensure high availability. However, PostgreSQL's streaming replication is more flexible, allowing you to replicate data between servers with different configurations and versions.


Indexing is creating data structures that allow for quick and efficient data retrieval. Both MongoDB and PostgreSQL support indexing, but they do it differently. MongoDB uses automatic indexing, which automatically creates indexes for frequently used queries. PostgreSQL requires you to create indexes on columns that are frequently queried manually.

The advantage of MongoDB's automatic indexing is that it saves developers time and effort, as they don't need to worry about creating indexes for common queries. However, it can also create unnecessary indexes, slowing down writes and increasing storage requirements. PostgreSQL's manual indexing provides more control over how indexes are created and maintained, which can lead to better performance.

Choosing between MongoDB and PostgreSQL depends on the specific needs of the project. MongoDB is a great option for applications that handle large amounts of unstructured data and require high performance and scalability. On the other hand, PostgreSQL is ideal for applications that require complex queries, transactions, and data consistency.

Both databases have their strengths and weaknesses, and it's important to thoroughly evaluate the project's requirements before deciding. Regardless of the choice, it's important to consider the selected database's security, reliability, and maintainability.

  • MongoDB is a NoSQL database specialising in handling unstructured data, making it ideal for real-time analytics and big data applications.
  • PostgreSQL is a relational database that provides robust data consistency and ACID compliance, making it perfect for transactional applications and complex queries.
  • MongoDB uses dynamic schema, while PostgreSQL uses static schema, meaning that data can be inserted without a predefined structure in MongoDB. Still, it must conform to a defined structure in PostgreSQL.
  • Unlike MongoDB, PostgreSQL supports JOIN operations, which are essential for complex queries requiring information from multiple tables. However, MongoDB provides faster data retrieval and better scalability.

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Susith Nonis

Susith Nonis

I'm fascinated by the IT world and how the 1's and 0's work. While I venture into the world of Technology, I try to share what I know in the simplest way with you. Not a fan of coffee, a travel addict, and a self-accredited 'master chef'.

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Aleen Walsh

2024, Jun, 24

Great article! It's really helpful to see a clear comparison between MongoDB and PostgreSQL. MongoDB seems perfect for projects needing flexible schema and high scalability, while PostgreSQL shines with its strong data integrity and complex querying capabilities. It all boils down to the specific needs of the project. Thanks for breaking it down so well!