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Amazon DocumentDB vs Microsoft Azure Cosmos DB comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 25, 2026

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
6th
Average Rating
8.2
Reviews Sentiment
4.0
Number of Reviews
6
Ranking in other categories
No ranking in other categories
Microsoft Azure Cosmos DB
Ranking in Managed NoSQL Databases
1st
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
109
Ranking in other categories
Database as a Service (DBaaS) (4th), NoSQL Databases (2nd), Vector Databases (1st)
 

Mindshare comparison

As of April 2026, in the Managed NoSQL Databases category, the mindshare of Amazon DocumentDB is 7.1%, down from 9.9% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 15.6%, down from 15.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Managed NoSQL Databases Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Cosmos DB15.6%
Amazon DocumentDB7.1%
Other77.3%
Managed NoSQL Databases
 

Featured Reviews

Hemanth Perepi - PeerSpot reviewer
Technical Lead at Trianz
Supports high-level data management and secure migration
Over the past few months, I’ve been working closely with a managed database service, and a few features stood out as game changers for me and my team: MongoDB Compatibility – The seamless migration experience was a huge win. No need to rewrite code or change drivers, which meant less friction and faster adoption for our developers. Fully Managed Service – Patching, backups, and monitoring are all automated. This freed up our team to focus on building applications instead of managing infrastructure. Separation of Compute & Storage – The flexibility to scale compute and storage independently gave us both cost savings and better performance optimization. Multi-AZ High Availability – Automatic failover and cross-AZ replication gave us peace of mind with improved uptime and disaster recovery. Performance at Scale – Even with large datasets, performance has remained consistent. Read replicas and efficient indexing have been especially valuable for read-heavy workloads. Security – End-to-end encryption, VPC isolation, and IAM integration made enterprise-level security feel straightforward and reliable. Backup & Recovery – Point-in-time recovery with automated backups made data protection effortless.
reviewer2724105 - PeerSpot reviewer
Senior Director of Product Management at a tech vendor with 1,001-5,000 employees
Provides super sharp latency, excellent availability, and the ability to effectively manage costs across different tenants
For integrating Microsoft Azure Cosmos DB with other Azure products or other products, there are a couple of challenges with the current system. Right now, the vectors are stored as floating-point numbers within the NoSQL document, which makes them inefficiently large. This leads to increased storage space requirements, and searching through a vast number of documents in the vector database becomes quite costly in terms of RUs. While the integration works well, the expense associated with it is relatively high. I would really like to see a reduction in costs for their vector search, as it is currently on the expensive side. The areas for improvement in Microsoft Azure Cosmos DB are vector pricing and vector indexing patterns, which are unintuitive and not well described. I would also like to see the parameters of Fleet Spaces made more powerful, as currently, it's somewhat lightweight. I believe they've made those changes intentionally to better understand the cost model. However, we would like to take a more aggressive approach in using it. One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document. Additionally, you must specify the configuration of that vector when you create an instance of Microsoft Azure Cosmos DB. Once the database is set up, you can't change the vector configuration, which is incredibly limiting for experimentation. You want the ability to try different settings and see how they perform, as there are numerous use cases for storing more than one vector in a document. While interoperability within the vector database is acceptable—for example, I can search for vectors—I still desire a richer set of configuration options.

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."
"The product is fast and easy to use."
"There are many benefits to using Amazon DocumentDB, for example, regarding the price, you can start with a small database and when you need more performance, you can grow the database."
"Migrations are easy using this product."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"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."
"From a global distribution perspective, Microsoft Azure Cosmos DB is good and easy to handle."
"The high speed of Azure Cosmos DB compared to other competitors is remarkable."
"Change notification works well, and the ability to process documents in a scalable way is important. This means we can efficiently thread out different operations and meet our organizational performance and scalability needs."
"Microsoft Azure Cosmos DB simplifies the process of saving and retrieving data."
"The feature I have found most valuable in Microsoft Azure Cosmos DB is its scalability and speed."
"Cosmos DB is stable and easy to use."
"The user interface of Microsoft Azure Cosmos DB is the best part of the entire Microsoft ecosystem; I find it to be the best user interface you can ever hope for, especially when compared to AWS and GCP, which do not measure up as well."
"We primarily use Cosmos DB because it's a managed platform service, eliminating concerns about hosting and reliability."
 

Cons

"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."
"There's a bit of a learning curve at the beginning."
"There's a bit of a learning curve at the beginning."
"The technical support could be improved."
"Improvements for Amazon DocumentDB could focus on enhancing high availability, sharding methods, replication techniques, and automatic failover in case the primary goes down, as continuous backup is an excellent option for disaster recovery."
"Improvements for Amazon DocumentDB could focus on enhancing high availability, sharding methods, replication techniques, and automatic failover in case the primary goes down, as continuous backup is an excellent option for disaster recovery."
"However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging."
"The first one is the ability to assign role-based access control through the Azure portal for accounts to have contributor rights."
"We would like to see advancements in AI with the ability to benchmark vector search capabilities, ensuring it answers questions accurately. During our initial implementation, we faced challenges with indexing and sorting, which are natively available in other offerings but required specific configurations in Cosmos."
"We had some performance issues with a data segregation query. We worked closely with Microsoft to solve the problem of performance where, for example, one query had a delay of almost two or three minutes for this one use case. Microsoft tried to improve the product, but in the end, the solution was to change to MongoDB. MongoDB had better performance."
"Our use case was a failure with Microsoft Azure Cosmos DB, and we do not have any other opportunity to use Microsoft Azure Cosmos DB."
"In the long run, there should be an addition of more features, especially because this space is evolving quickly. It all boils down to how many more features you are adding, how many integrations you are supporting, and how many more APIs you have that are standard APIs."
"We expect Cosmos DB to lead on that. There is potential for improved security features, which is important for data storage, especially for Dell Technologies."
"If you want to bring the data from AWS, you must pay data egress costs. That's a pain point."
"One of the primary challenges with Cosmos DB as a non-relational data store is the careful data modeling required due to the lack of collection-level joins when using the SQL API."
 

Pricing and Cost Advice

Information not available
"Because of the lack of understanding about RUs, the costs become unpredictable. It sometimes goes over the budget."
"Its price is in the middle, neither too low nor too high."
"The pricing for Microsoft Azure Cosmos DB is good. Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective."
"When we've budgeted for our resources, it's one of the more expensive ones, but it's still not very expensive per month."
"The pricing is perceived as being on the higher side. However, if you have large data operations, it might reduce costs due to performance efficiencies."
"It's expensive. I would rate it a seven out of ten for pricing."
"Azure is a pay as you go subscription."
"The RU's use case determines our license fees."
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
12%
Manufacturing Company
11%
Government
8%
Legal Firm
11%
Financial Services Firm
11%
Comms Service Provider
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business33
Midsize Enterprise22
Large Enterprise58
 

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 pricing and licensing of Amazon DocumentDB is managed directly by the client team with the vendor, so I am not involved in that aspect.
What is your experience regarding pricing and costs for Microsoft Azure Cosmos DB?
Microsoft Azure Cosmos DB's pricing model has aligned with my budget expectations because I can tune the RU as I need to, which helps a lot. Microsoft Azure Cosmos DB's dynamic auto-scale or server...
What needs improvement with Microsoft Azure Cosmos DB?
I have not utilized Microsoft Azure Cosmos DB multi-model support for handling diverse data types. I'm not in the position to decide if clients will use Microsoft Azure Cosmos DB or any other datab...
What is your primary use case for Microsoft Azure Cosmos DB?
We have a very large team of developers who develop a solution for our customers. In the part where they need some infrastructure on Microsoft Azure, we deploy entire environments of different type...
 

Also Known As

No data available
Microsoft Azure DocumentDB, MS Azure Cosmos DB
 

Overview

 

Sample Customers

Finra, The Washington Post, Freshop
TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify
Find out what your peers are saying about Amazon DocumentDB vs. Microsoft Azure Cosmos DB and other solutions. Updated: April 2026.
890,071 professionals have used our research since 2012.