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.

MongoDB

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Amazon DynamoDB

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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 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

-0.56

Rather negative sentiment
Customer Service

No data

+0.6

Rather positive sentiment
Ease of Use

+1

Strongly positive sentiment

+0.69

Rather positive sentiment
Reliability and Performance

+0.56

Rather positive sentiment

+0.6

Rather positive sentiment
Ease of Implementation

+0.56

Rather positive sentiment

+0.56

Rather 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

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

PostgreSQL

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.

ScyllaDB

ScyllaDB is a database designed for applications that need to handle massive amounts of data with very fast response times. Think of it like a super-efficient filing system that’s always lightning fast, even with billions of files. It's ideal for companies experiencing rapid growth that need to ensure their systems remain fast and reliable as they add more users and data. ScyllaDB boasts lower operating costs compared to other databases and is used by companies like Disney+ and Expedia.

Couchbase

Couchbase is a versatile database designed for modern, data-intensive applications. Its strength lies in handling various data types efficiently, making it suitable for applications requiring speed and scalability. This adaptability simplifies data management and allows developers to use their preferred tools. While Couchbase serves diverse industries, it's particularly beneficial for companies with high-performance needs like real-time analytics and personalized user experiences. Its flexible deployment model accommodates both cloud-based and on-premise preferences.

MariaDB

MariaDB is a popular, free alternative to traditional database software. Developed by the creators of MySQL, it's known for its strong performance, reliability, and open-source nature. MariaDB is highly adaptable, working well for both transaction-heavy tasks (like processing orders) and analyzing large datasets. It's commonly used by companies of all sizes and is a key part of many cloud computing services. Notably, MariaDB offers similar features as more expensive database products but without the high cost.

Aiven for Apache Cassandra

Aiven for Apache Cassandra is a cloud-based database solution designed for businesses that need to manage large amounts of data. It offers a fully managed service, meaning Aiven takes care of the technical complexities so you don't have to. This allows your team to focus on using the data, not managing the database. Aiven for Apache Cassandra is secure, reliable, and integrates seamlessly with popular cloud providers like AWS, Google Cloud, and Microsoft Azure.

Microsoft SQL Server

Microsoft SQL Server is a database management system for businesses of all sizes. It helps you analyze various types of data and can be used in multiple environments, including on your servers and in the cloud. SQL Server offers high performance and strong security features. It allows developers to build applications using different programming languages and provides mobile business intelligence tools.

Page co-authored by

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.

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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