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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."
"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."
"Amazon DocumentDB is a simple solution."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"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."
"The best part of Microsoft Azure Cosmos DB is that with the default configuration and the Azure functional pipeline, if your go-to cloud provider is Microsoft Azure, the whole integration is seamless."
"We love the ability to land data with Cosmos DB easily. Cosmos is native to Azure, so everything works seamlessly with it. You need good data to have good AI, and Cosmos makes it easy to land the data."
"I appreciate Microsoft Azure Cosmos DB's robust document management and consistent availability."
"What I appreciate most are the latency and the access, which are guaranteed by the tool, which is really impressive."
"The standout features are its ability to do data compression easily and the ability to scale horizontally."
"The solution is extremely user-friendly and easy to navigate."
"Azure Cosmos DB offers numerous data connectors that provide a platform for seamless integration with various platforms and visualization tools such as Power BI. It allows connection via multiple data connectors to integrate data in any desired format."
"Microsoft Azure Cosmos DB's most valuable feature is latency."
 

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."
"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."
"However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging."
"The technical support could be improved."
"The size of the continuation token in Azure Cosmos DB should be static rather than increasing with more data, as it can lead to application crashes. They should use a static key size."
"We should have more freedom to tweak it and make our own queries for non-traditional use-cases."
"One area of improvement for Cosmos database is the auto-scaling of RUs during high loads. It would be beneficial if the database could automatically scale resources rather than requiring manual adjustments."
"From about half a billion rows, we're returning maybe 20,000 in two or three minutes. We don't know why, but we are working with Microsoft and a third party to figure that out."
"The cost is a concern. Microsoft Azure Cosmos DB did not decrease our total cost of ownership. From the standpoint of the old way of doing DBA operations, it did, but our cloud cost increased significantly."
"If we have a lot of data, doing a real-time vector search is a performance challenge because the search happens over a large dataset. It consumes more time."
"One area that could be improved is indexing. Some of the developers struggle with the way the indexing works. We are exploring vector indexing, which we haven't examined fully yet. Indexing is an aspect we're looking to improve upon potentially."
"The model with autoscaling for RU is complicated to optimize RU consumption."
 

Pricing and Cost Advice

Information not available
"It's expensive. I would rate it a seven out of ten for pricing."
"The pricing and licensing model was initially difficult to understand, but as soon as I learned what was going on and how it was priced, it was pretty easy."
"Cosmos should be cheaper. We actually intend to stop using it in the near future because the price is too high."
"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."
"Its cost is transparent. Pricing depends on the transaction and data size, but overall, it is cheaper compared to hosting it on your corporate network due to other factors like power consumption."
"Cosmos DB is expensive, and the RU-based pricing model is confusing. Although they have a serverless layer, there are deficiencies in what I can define and assign to a database. Estimating infrastructure needs is not straightforward, making it challenging to manage costs."
"Its pricing structure is quite flexible."
"The price of Microsoft Azure Cosmos DB could be a bit lower."
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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: February 2026.
883,824 professionals have used our research since 2012.