MongoDB vs PostgreSQL

by Gralio Feb 27, 2025

MongoDB and PostgreSQL cater to different data management needs. MongoDB prioritizes flexibility and scalability for unstructured data, ideal for modern applications and agile development. PostgreSQL emphasizes data integrity and relational structure, suitable for transactional systems and applications requiring strong ACID properties.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 1466 reviews and 60 websites, saving 8 hours, 38 minutes of reading.

Logo of MongoDB
Logo of PostgreSQL

About

MongoDB is a flexible database management software designed for modern businesses. Unlike traditional systems that rely on rigid tables, MongoDB stores data as documents, similar to how we organize information in files. This makes it easier for developers to build applications and adapt to changing needs. MongoDB excels at handling large volumes of diverse data, making it suitable for various tasks like real-time analytics and managing online catalogs.
PostgreSQL is a reliable, open-source database system businesses use to store and manage their data. Known for its reliability and performance, it's suitable for a wide range of needs, from single computers to large-scale data storage for multiple users. PostgreSQL is free to use and is backed by a large community of developers.

Summary

Main difference
MongoDB is better for businesses needing a flexible, schema-less database for handling large volumes of unstructured data, particularly in the software and IT sectors. PostgreSQL is better for applications requiring strong data integrity, relational data structures, and ACID properties, making it suitable for financial and e-commerce applications.

Relative strengths of MongoDB (compared to PostgreSQL)

  • Flexible Schema: Adapts easily to evolving data structures, simplifying development and allowing for faster iterations.

  • Scalability: Handles large volumes of data and high traffic loads efficiently, suitable for growing businesses.

  • Ease of Use for Developers: The document-oriented model aligns well with how developers structure data in applications, making it easier to work with.

Relative weaknesses of MongoDB (compared to PostgreSQL)

  • Limited JOIN Support: Complex queries involving relationships between data can be challenging.

  • Higher Memory Consumption: Can require more memory compared to relational databases, impacting infrastructure costs.

  • Steeper Learning Curve for SQL Users: Requires learning a new query language and data model, potentially increasing training time.

Who is using MongoDB and PostgreSQL?

Piotr Smolen
CEO at symmetrical.ai
No data

Who should use MongoDB VS. PostgreSQL

MongoDB is a versatile database solution designed for modern businesses seeking flexibility and scalability. Its document-based model simplifies development and adapts to evolving data structures. Users praise its flexible schema and powerful query language but note the learning curve and limited JOIN support. A strong choice for handling large datasets and real-time analytics.

PostgreSQL is a powerful, open-source database known for its reliability and performance. Users appreciate its efficient handling of large datasets and fast query times. It's an excellent choice for businesses of all sizes needing a robust and scalable database solution. However, some users find the initial setup complex and the CPU usage somewhat high.

  • Ideal for small to large businesses (1-1000+ employees).

  • Best fit for Software, IT & Telecommunications.

  • Excellent fit for small, medium, and large businesses.

  • Ideal for IT, suitable for e-commerce, retail, and public sector, less suitable for industries like healthcare, manufacturing, and logistics.

MongoDB and PostgreSQL features

Supported
Partially supported
Not supported
Type in the name of the feature or in your own words tell us what you need

  • Object-relational database
    Not supported

    MongoDB is a NoSQL document database, not an object-relational database.

    Supported

    PostgreSQL is an object-relational database management system (ORDBMS).

  • Data Storage
    Supported

    MongoDB stores data centrally using a document-oriented model.

    Supported

    PostgreSQL is a relational database, organizing data in tables for efficient centralized storage.

  • Data Retrieval
    Supported

    MongoDB supports efficient data retrieval with its query system, indexing, and aggregation framework.

    Supported

    PostgreSQL allows efficient data retrieval with SQL queries, indexing, and query optimization.

  • SQL support
    Partially supported

    MongoDB does not support SQL directly, but offers SQL-like querying via tools like the BI Connector and Atlas SQL Interface.

    Supported

    PostgreSQL, as offered via EDB on AWS Marketplace, fully supports SQL querying.

  • NoSQL support
    Supported

    MongoDB is a NoSQL database, it natively supports querying data stored within it.

    Not supported

    PostgreSQL does not have built-in support for querying data in NoSQL databases like MongoDB or Cassandra. However, it offers NoSQL-like capabilities through its support for JSON and JSONB data types, enabling it to handle and query semi-structured data in a manner similar to NoSQL databases.

  • PL/SQL support
    Not supported

    MongoDB does not support PL/SQL, which is specific to Oracle databases. While Oracle provides an API for MongoDB, it allows using SQL within MongoDB, not PL/SQL.

    Not supported

    PostgreSQL does not support PL/SQL for querying Oracle databases. It uses its own procedural language, PL/pgSQL.

Qualities

  • Value and Pricing Transparency
    +0.33
    Rather positive sentiment
    +1
    Strongly positive sentiment
  • Customer Service
    No data
    +0.33
    Rather positive sentiment
  • Ease of Use
    +1
    Strongly positive sentiment
    +0.69
    Rather positive sentiment
  • Reliability and Performance
    +0.56
    Rather positive sentiment
    +0.54
    Rather positive sentiment
  • Ease of Implementation
    +0.56
    Rather positive sentiment
    +0.56
    Rather positive sentiment
  • Scalability
    +0.83
    Strongly positive sentiment
    +0.71
    Strongly positive sentiment

MongoDB and PostgreSQL Pricing

No data

See full Pricing page

No data
We couldn't find a pricing page for PostgreSQL.

MongoDB and PostgreSQL review insights

Users love

  • Flexible schema design, allowing for evolving data structures
  • Scalability and efficient handling of large datasets
  • Powerful query language and aggregation framework
  • Active community and extensive documentation
  • Open-source database
  • Easy to install and configure
  • Handles large datasets efficiently
  • Fast querying time
  • Strong community support

Users dislike

  • Limited JOIN support, making complex queries challenging
  • High memory consumption, especially with large datasets
  • Steep learning curve for beginners, especially those familiar with SQL databases
  • Backup and restore operations can be complex compared to traditional relational databases
  • Consumes somewhat higher CPU usage so that efficiency is a bit low
  • Initial setup is not straightforward.
  • Limited GUI tools.
  • PostgreSQL may have slower performance than other RDBMS like SQL Server and MySQL.

MongoDB and PostgreSQL Ratings

  • G2
    4.6/5
    (17)
  • Capterra
    4.7/5
    (458)
  • G2
    4.4/5
    (635)
  • Capterra
    4.6/5
    (360)

Company health

Employee growth

5% increase in the last year
1% increase in the last year

Web traffic

3% decrease in the last quarter
2% decrease in the last quarter

Financing

No data
No data

How important is strict schema enforcement for your data integrity?

Strict schema enforcement is crucial for data integrity if you prioritize consistency and reliability. PostgreSQL, with its relational structure and SQL foundation, enforces a strict schema, ensuring data conforms to predefined rules and minimizing inconsistencies. MongoDB, being schema-less, offers flexibility but may increase the risk of data integrity issues if not carefully managed. Therefore, if strict enforcement is a primary concern, PostgreSQL is the more suitable choice.

Which database better suits your team's existing SQL expertise?

PostgreSQL better suits a team with existing SQL expertise. PostgreSQL is a relational database that uses standard SQL syntax, while MongoDB is a NoSQL database with its own query language. For a team already familiar with SQL, PostgreSQL will require significantly less training and allow them to leverage their existing skills.

What are the advantages of MongoDB?

MongoDB offers advantages in terms of flexibility and scalability. Its document-oriented data model makes it easier for developers to adapt to evolving data structures and handle diverse data types, unlike PostgreSQL's rigid relational model. MongoDB is also known for its ability to scale horizontally and handle large datasets efficiently, making it suitable for modern applications with high data volume and velocity. While PostgreSQL excels in data integrity and ACID compliance, MongoDB prioritizes flexibility and scalability for rapid development and evolving data needs.

What are the disadvantages of MongoDB?

MongoDB has limited JOIN support, making complex queries challenging. It also has high memory consumption, particularly with large datasets. Users have reported a steep learning curve, especially for those familiar with SQL databases. Finally, backup and restore operations can be more complex compared to traditional relational databases.

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Page co-authored by
MK
Michal Kaczor
CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

TT
Tymon Terlikiewicz
CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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