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Amazon DocumentDB vs MongoDB Atlas comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 3, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Amazon DocumentDB
Ranking in Managed NoSQL Databases
5th
Average Rating
8.4
Reviews Sentiment
7.7
Number of Reviews
3
Ranking in other categories
No ranking in other categories
MongoDB Atlas
Ranking in Managed NoSQL Databases
6th
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
48
Ranking in other categories
Database as a Service (DBaaS) (3rd)
 

Mindshare comparison

As of April 2025, in the Managed NoSQL Databases category, the mindshare of Amazon DocumentDB is 10.3%, down from 13.8% compared to the previous year. The mindshare of MongoDB Atlas is 5.7%. It is calculated based on PeerSpot user engagement data.
Managed NoSQL Databases
 

Featured Reviews

Javed Zahoor - PeerSpot reviewer
Offers the ability to replicate data across different instances
Its speed has had the most significant impact on our projects. For starters, we used it for its flexibility. With DocumentDB, you're not tied to a rigid structure like you are with Aurora or other relational databases. This makes it great for startups. When we work with established systems where the structure is well-defined, the speed of DocumentDB becomes the most important factor. Compared to a relational database, scaling DocumentDB is easier because of its ability to replicate data across different instances. If you use a network-based storage service with your cluster, the primary instance doesn't even need a full local copy of the data, since it's accessible on the shared storage. That definitely contributes to scalability. AWS-managed services already handle a lot of the scaling complexity. We don't have to do anything.
Laksiri Bala - PeerSpot reviewer
Room for improvement in data handling leads to enhanced cost-effective data management performance
It would be beneficial if MongoDB Atlas could better support OLTP aspects and data frames, as well as enhance its capabilities for data pipelines and visualization dashboards. Furthermore, supporting the medallion architecture could be a valuable addition, and incorporating improved spatial and vector handling for geographical data could make it more competitive. Enhancing vector processing for AI capabilities would also be critical.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Amazon DocumentDB is a simple solution."
"Migrations are easy using this product."
"Its speed has had the most significant impact on our projects. For starters, we used it for its flexibility. With DocumentDB, you're not tied to a rigid structure like you are with Aurora or other relational databases. This makes it great for startups."
"MongoDB Atlas is a database that is quite fast, stable, and reliable."
"It is nice because our developers create tables whenever they need to sync data."
"The product allows us to easily set up and store large amounts of unstructured data."
"As a tester, it was easy to validate data, access data, make active run queries against it, and retrieve data from it."
"There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple features, including built-in backup, all under the same roof, without the need for external tools."
"The solution is easy to use, the console is user-friendly, and overall a well-designed solution. It takes a complex system and makes it easy to understand. Additionally, the solution is always advancing and they provide a roadmap into what is coming in the future."
"The key feature of MongoDB Atlas that has been helpful for us is the ease of deploying new databases."
"It is a scalable solution because we use quite a lot of data, and it handles it well."
 

Cons

"The technical support could be improved."
"There's a bit of a learning curve at the beginning."
"One possible improvement could be a hybrid database solution, where parts of the application leverage a relational database alongside DocumentDB. If a system were heavily relational in nature, a database like PostgreSQL might be a good fit."
"The initial configuration fine-tuning for performance can be time-consuming."
"The tool's implementation should be made easier."
"If it could be cheaper, that would make us happy."
"The replica side, like the venue, can be improved."
"The cost needs improvement. The product is good, but the cost that we paid for it is expensive, so it wasn't that valuable."
"I would like to have better performance for user experience with the solution."
"Customer support needs improvement knowledge-wise."
"A few areas that we have noticed as being problematic with the MongoDB Atlas include user access to the platform. Currently, it is difficult to restrict and control what actions a user can perform within the solution, which poses a challenge from an internal auditing perspective."
 

Pricing and Cost Advice

Information not available
"MongoDB Atlas is more cost-effective than Amazon DocumentDB. It also has a pay-as-you-go pricing model. Apart from the standard licensing cost, you must also pay to get MongoDB Atlas technical support, which is expensive."
"We pay for a license."
"The pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones."
"The solution is fairly priced. I rate the pricing a seven out of ten."
"The pricing is good. We originally chose it over DynamoDB because of the pricing."
"For me, MongoDB is expensive, but I think it is not so expensive for customers."
"It is an open-source platform."
"It is too expensive. They need to work on this."
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Top Industries

By visitors reading reviews
Computer Software Company
22%
Financial Services Firm
18%
Manufacturing Company
11%
Government
6%
Computer Software Company
19%
Financial Services Firm
15%
Comms Service Provider
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What advice do you have for others considering Amazon DocumentDB?
Amazon DocumentDB offers us many useful features. It is definitely a solution that an organization in need of comprehensive and effective document management should invest its money into. We are im...
What do you like most about Amazon DocumentDB?
Its speed has had the most significant impact on our projects. For starters, we used it for its flexibility. With DocumentDB, you're not tied to a rigid structure like you are with Aurora or other ...
What is your experience regarding pricing and costs for Amazon DocumentDB?
The specific DocumentDB implementation we use is on the expensive side. We tend to use it strategically in complex systems, primarily for lookup capabilities. For simpler use cases, we often choose...
What do you like most about MongoDB Atlas?
There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple featu...
What is your experience regarding pricing and costs for MongoDB Atlas?
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
What needs improvement with MongoDB Atlas?
It would be beneficial if MongoDB Atlas could better support OLTP aspects and data frames, as well as enhance its capabilities for data pipelines and visualization dashboards. Furthermore, supporti...
 

Also Known As

No data available
Atlas
 

Overview

 

Sample Customers

Finra, The Washington Post, Freshop
Wells Fargo, Forbes, Ulta Beauty, Bosch, Sanoma, Current (a Digital Bank), ASAP Log, SBB, Zebra Technologies, Radial, Kovai, Eni, Accuhit, Cognigy, and Payload.
Find out what your peers are saying about Amazon DocumentDB vs. MongoDB Atlas and other solutions. Updated: April 2025.
849,475 professionals have used our research since 2012.