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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
5th
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 March 2026, in the Managed NoSQL Databases category, the mindshare of Amazon DocumentDB is 7.4%, down from 10.1% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 16.0%, down from 16.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Managed NoSQL Databases Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Cosmos DB16.0%
Amazon DocumentDB7.4%
Other76.6%
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."
"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."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Amazon DocumentDB is a simple solution."
"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 high speed of Azure Cosmos DB compared to other competitors is remarkable."
"Our team has found the vCore index to be one of the most valuable features. We have tokenized and vectorized our entire database and stored this data in MongoDB collections with a vCore index, which works like magic for keyword selection."
"Cosmos is preferred because of its speed, robustness, and utilization."
"It's highly scalable and supports consistency, security, and multiple security options."
"The solution is used because we get faster response times with large data sets than with SQL."
"It is a scalable product."
"Microsoft Azure Cosmos DB simplifies the process of saving and retrieving data."
"Azure Cosmos DB offers efficient indexing and low search latency, making searching fast and efficient and ensuring peace of mind in database operations."
 

Cons

"The technical support could be improved."
"However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging."
"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."
"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."
"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."
"Continuing to educate customers on how they can take better advantage of Microsoft Azure Cosmos DB without having to completely rewrite their entire application paradigm would be beneficial. They can help them understand that there are multiple options to interact with it. They do not necessarily have to start from scratch. They can refactor their existing application to be able to use it better."
"There is room for improvement in Microsoft's maintenance aspect. For example, we had a major incident at the end of December where the entire South Central region was down for our application, causing many problems due to a lack of access to the database."
"There is room for improvement in terms of stability."
"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."
"Azure Cosmos DB is generally a costly resource compared to other Azure resources. It comes with a high cost."
"There are no particular factors that need improvement. There is a little bit of a learning curve with scaling workloads, but it works smoothly."
"The operational complexity of Microsoft Azure Cosmos DB can be challenging for individuals who are not tech-savvy."
"If you want to bring the data from AWS, you must pay data egress costs. That's a pain point."
 

Pricing and Cost Advice

Information not available
"The RU's use case determines our license fees."
"This cost model is beneficial because it allows for cost control by limiting resource units (RUs), which is ideal. However, for our needs, we can't engage with their minimum pricing, which ranges from 100 to 1,000 RUs. At the bare minimum, we need to use 4,000 RUs for a customer. I would like to find a way to gain some advantages from the lowest tier, particularly the ability to scale down if necessary. It would be helpful to have more flexibility in cost management at the lower end."
"Its pricing is not bad. It is good."
"If you are a small organization or startup building from scratch without the Microsoft Startup Founder Club support, it could be expensive."
"The pricing model of Microsoft Azure Cosmos DB is a bit complex."
"Microsoft provides fair pricing."
"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."
"Its pricing structure is quite flexible."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
13%
Manufacturing Company
10%
Educational Organization
7%
Legal Firm
12%
Financial Services Firm
10%
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.
884,706 professionals have used our research since 2012.