MongoDB vs Amazon DynamoDB

by Gralio Mar 12, 2025

MongoDB and Amazon DynamoDB are both popular NoSQL databases catering to different needs. MongoDB offers flexibility and powerful querying, ideal for businesses with evolving data structures and complex analytical requirements. DynamoDB prioritizes scalability, performance, and ease of management within the AWS cloud, best suited for applications requiring minimal operational overhead and seamless integration with other AWS services.

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 1092 reviews and 60 websites, saving 6 hours, 34 minutes of reading.

Logo of MongoDB
Logo of Amazon DynamoDB

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.
Amazon DynamoDB is a fully managed database service that's part of the Amazon Web Services (AWS) cloud platform. It's designed to handle massive amounts of data and traffic, making it suitable for businesses with demanding applications, like mobile apps or e-commerce platforms. Unlike traditional databases, DynamoDB doesn't rely on servers, meaning it can scale its resources up or down automatically based on your needs. This ensures fast performance, high availability, and cost-efficiency as you only pay for what you use.

Summary

Main difference
MongoDB offers greater flexibility in schema design and querying, suiting businesses with evolving data structures and complex data relationships. DynamoDB excels in providing a fully managed, highly scalable, and performant database service within the AWS ecosystem, ideal for applications requiring minimal operational overhead and seamless integration with other AWS services.

Relative strengths of MongoDB (compared to Amazon DynamoDB)

  • Flexible schema allows for easier adaptation to changing data needs.

  • More powerful querying and aggregation capabilities for complex data analysis.

  • Active community and extensive documentation provide strong support resources.

Relative weaknesses of MongoDB (compared to Amazon DynamoDB)

  • Requires more hands-on management compared to DynamoDB's fully managed service.

  • Can be more complex to set up and maintain, demanding specialized expertise.

  • Higher memory consumption can impact cost-efficiency, especially with large datasets.

Who is using MongoDB and Amazon DynamoDB?

Piotr Smolen
CEO at symmetrical.ai
No data

Who should use MongoDB VS. Amazon DynamoDB

MongoDB is a versatile database solution popular for its flexible schema design and ability to handle large datasets efficiently. Developers praise its powerful query language and active community support, while some note challenges with JOIN operations and memory consumption. It's ideal for businesses of all sizes needing scalable data management for real-time analytics and evolving application development.

Amazon DynamoDB is a serverless NoSQL database service renowned for its scalability and speed. Users praise its fully managed nature and seamless integration with other AWS services. However, some find its pricing complex and querying capabilities limited. DynamoDB is well-suited for businesses with high-volume applications needing low-latency data access, like mobile apps or e-commerce platforms.

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

  • Best fit for Software, IT & Telecommunications; less suitable for industries like Healthcare, Finance, or E-commerce.

  • Ideal for small to large businesses seeking a scalable NoSQL database solution.

  • Best fit for software, IT, and telecommunications; suitable for e-commerce and education.

MongoDB and Amazon DynamoDB features

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

  • Data Storage
    Supported

    MongoDB stores data centrally using a document-oriented model.

    Supported

    DynamoDB systematically stores data in a centralized location within AWS.

  • Data Retrieval
    Supported

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

    Supported

    DynamoDB allows efficient data retrieval through queries, especially using key-value lookups.

  • NoSQL
    Supported

    MongoDB is a NoSQL database, so it does not require a predefined schema, normalization, or SQL.

    Supported

    DynamoDB is a NoSQL database, so it does not require schema definition or data normalization.

  • Cloud-based deployment
    Supported

    MongoDB supports cloud-based deployments through products like Atlas and Cloud Manager.

    Supported

    DynamoDB is deployed and managed within the AWS cloud environment.

  • NoSQL support
    Supported

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

    Not supported

    DynamoDB is a NoSQL database but it does not support querying other NoSQL databases.

  • Scalability options
    Supported

    MongoDB supports both vertical and horizontal scaling, along with automated scaling features in MongoDB Atlas, enabling scaling up or down based on needs.

    Supported

    DynamoDB allows scaling capacity up or down automatically or by setting limits, based on needs.

Qualities

  • Value and Pricing Transparency
    +0.33
    Rather positive sentiment
    -0.6
    Rather negative sentiment
  • Customer Service
    No data
    +0.67
    Rather positive sentiment
  • Ease of Use
    +1
    Strongly positive sentiment
    +0.56
    Rather positive sentiment
  • Reliability and Performance
    +0.56
    Rather positive sentiment
    +0.6
    Rather positive sentiment
  • Ease of Implementation
    +0.56
    Rather positive sentiment
    +0.71
    Strongly positive sentiment
  • Scalability
    +0.83
    Strongly positive sentiment
    +1
    Strongly positive sentiment

MongoDB and Amazon DynamoDB Pricing

No data

User sentiment

Rather positive
+0.33

See full Pricing page

No data

User sentiment

Rather negative
-0.56

See full Pricing page

MongoDB and Amazon DynamoDB review insights

1092 reviews analysed from and

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
  • Fully managed service, no need for manual server maintenance.
  • High scalability and availability for demanding applications.
  • Fast performance with low-latency data access.
  • Flexible NoSQL data model for evolving schemas.
  • Seamless integration with other AWS services like Lambda and S3.

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
  • Limited querying options, making complex searches difficult.
  • High costs, especially for read/write capacity units.
  • Steep learning curve for data modeling and efficient querying.
  • Limited local development options and testing capabilities.
  • Vendor lock-in to the AWS ecosystem.

MongoDB and Amazon DynamoDB Ratings

  • G2
    4.6/5
    (17)
  • Capterra
    4.7/5
    (458)
  • G2
    4.4/5
    (617)
  • Glassdoor
    3.7/5
    (206324)

Company health

Employee growth

5% increase in the last year
12% increase in the last year

Web traffic

11% decrease in the last quarter
3% decrease in the last quarter

Financing

No data
No data

How does each product's scaling approach impact application performance?

MongoDB's scaling approach, utilizing sharding and replica sets, allows for horizontal scaling, distributing data across multiple servers to improve performance with growing datasets. However, complex queries involving joins can be challenging due to data distribution. DynamoDB, being a serverless database, automatically scales capacity based on demand, ensuring consistent performance even with fluctuating workloads. However, this automatic scaling can lead to unpredictable costs, and the simplified data model can limit complex query capabilities.

Which product better simplifies complex query needs for diverse datasets?

MongoDB better simplifies complex query needs for diverse datasets due to its more robust querying and aggregation framework. While DynamoDB excels at key-value lookups for simple queries, MongoDB's document model and query language offer greater flexibility for complex searches and data analysis across varied data structures. Although MongoDB has limitations with JOINs, its overall querying capabilities are more extensive than DynamoDB's, making it more suitable for handling diverse datasets and intricate queries.

What are the advantages of MongoDB?

MongoDB offers a flexible schema design, beneficial for evolving data structures, along with scalability for large datasets. It also provides a powerful query language and aggregation framework. Finally, MongoDB benefits from an active community and extensive documentation, which aids developers.

What are the disadvantages of MongoDB?

MongoDB has some drawbacks, including limited JOIN support for complex queries, high memory consumption with large datasets, a steep learning curve for users familiar with SQL databases, and complex backup and restore processes. Users also mention that it can be challenging for beginners.

Alternatives to MongoDB and Amazon DynamoDB

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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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