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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

"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Amazon DocumentDB is a simple solution."
"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."
"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."
"The product is fast and easy to use."
"Migrations are easy using this product."
"The biggest benefit of Microsoft Azure Cosmos DB is the general cloud model that Azure gives you, providing more flexibility from a cost and data perspective while offering reasonable pricing and the best security solutions with zero trust protection, and with Azure you can start small and grow as you need."
"Cosmos DB is a pretty stable solution. I would rate it a ten out of ten."
"I like the scalability. There aren't any constraints for posting in the geolocation. I also like the SQL architecture."
"The dynamic autoscale or serverless model of Microsoft Azure Cosmos DB has indeed helped reduce our costs and operational effort by allowing us to scale horizontally in a straightforward manner according to our needs."
"We have both our SaaS app and the analytical side running without throttling issues."
"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."
"Microsoft Azure Cosmos DB has helped decrease my company's total cost of ownership; it's easier because we have less to maintain, we're not trying to set up multiple SQL servers with replication and everything, and centralization helps a lot."
"From a global distribution perspective, Microsoft Azure Cosmos DB is good and easy to handle."
 

Cons

"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."
"The technical support could be improved."
"There's a bit of a learning curve at the beginning."
"There's a bit of a learning curve at the beginning."
"However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging."
"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."
"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 tool's pricing is expensive."
"The only problem I face is more with infrastructure as code templates that don't cover everything that can be set up or configured on the portal, requiring some manual work which is additional work for us."
"The operational complexity of Microsoft Azure Cosmos DB can be challenging for individuals who are not tech-savvy."
"The built-in integration of the solution is tight."
"One of our biggest pain points is the backup and restore functionality needs improvement. They've gotten a little better in this area. SQL Server's long-term retention is amazing, and you can restore data from years ago. You need to open a support Microsoft ticket to restore your Cosmos DB backup, and it comes in on a different Cosmos account. It's just kind of a headache to restore data."
"The only area Microsoft Azure Cosmos DB can improve on is its documentation; while it is solid and very useful, enhancements in the indexing documentation would help users save costs and make it more cost-effective."
"Slight enhancements in integration interfaces, expanded dashboard functionalities, and broader use-case support would be beneficial."
"The integration of the on-premise solution with the cloud can be difficult sometimes."
 

Pricing and Cost Advice

Information not available
"Its pricing is not bad. It is good."
"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 is cost-efficient as long as you understand the right setup to optimize usage. Knowing the data needs of the organization and adjusting the Microsoft Azure Cosmos DB usage accordingly helps save costs, but if you don't know, you could end up spending more than necessary."
"Its price is very good for the basic stuff. When you go to a more complicated use case, especially when you need replication and availability zones, it gets a little costly."
"There is a licensing fee."
"Its price is in the middle, neither too low nor too high."
"Azure is a pay as you go subscription."
"The tool is not expensive."
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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
12%
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 do you like most about Microsoft Azure Cosmos DB?
The initial setup is simple and straightforward. You can set up a Cosmos DB in a day, even configuring things like availability zones around the world.
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...
 

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: March 2026.
886,858 professionals have used our research since 2012.