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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

"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."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"The product is fast and easy to use."
"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."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Amazon DocumentDB is a simple solution."
"Migrations are easy using this product."
"When all resources are at the same point, there is no lag and in production we have experienced minimal issues, with the project live for two years without any database problems."
"It is a cloud-based solution that is easy to deploy, easy to access, and provides users with more features compared to other clouds like AWS and GCP."
"The product has a lot of useful features that are there and ready to use, it's also very easy to use."
"The fact that scalability can be achieved by simply configuring availability zones is very attractive."
"The most valuable aspect of Cosmos DB is its performance."
"What I appreciate most are the latency and the access, which are guaranteed by the tool, which is really impressive."
"The solution is easy to use, and it is also easy to integrate with several things for database use cases."
"Overall, I would rate it a nine out of ten with the only significant issue being the partitioning key functionality."
 

Cons

"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."
"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."
"We'd like to avoid full DR replication if possible, as this would result in significant cost savings."
"The solution cannot join two databases like Oracle or SQL Server."
"There should be a simpler way for data migration."
"One area for improvement is the ease of writing SQL queries and stored procedures in Microsoft Azure Cosmos DB."
"Better documentation on how to integrate with other components would be helpful because I was struggling with this."
"While Microsoft Azure Cosmos DB is generally easy to use, it has some limitations."
"Azure Cosmos DB is generally a costly resource compared to other Azure resources. It comes with a high cost."
"One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document."
 

Pricing and Cost Advice

Information not available
"Pricing, at times, is not super clear because they use the request unit (RU) model. To manage not just Azure Cosmos DB but what you are receiving for the dollars paid is not easy. It is very abstract. They could do a better job of connecting Azure Cosmos DB with the value or some variation of that."
"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."
"Azure Cosmos DB's pricing is competitive, though there is a need for more personalized pricing models to accommodate small applications without incurring high charges. A suggestion is to implement dynamically adjustable pricing that accounts for various user needs."
"It is expensive. The moment you have high availability options and they are mixed with the type of multitenant architecture you use, the pricing is on the higher end."
"From a startup point of view, it appears to be expensive. If I were to create my startup, it would not have the pricing appeal compared to the competition, such as Supabase. All those other databases are well-advertised by communities. I know there is a free tier with Azure Cosmos DB. It is just not well advertised."
"Everything could always be cheaper. I like that Cosmos DB allows us to auto-scale instead of pre-provisioning a certain capacity. It automatically scales to the demand, so we only pay for what we consume."
"Cosmos DB is a highly cost-optimized solution when used correctly."
"Cosmos should be cheaper. We actually intend to stop using it in the near future because the price is too high."
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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.
886,906 professionals have used our research since 2012.