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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

"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."
"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."
"Migrations are easy using this product."
"It is easy to use because you don't need to know much about Cosmos DB or have prior experience."
"Microsoft Azure Cosmos DB's most valuable feature is latency."
"Reading and inserting data into Microsoft Azure Cosmos DB is a very smooth process."
"The autoscale feature is the most useful for us."
"The peace of mind that Microsoft Azure Cosmos DB provides regarding global distribution is invaluable."
"The scalability and ease of use with the APIs of Microsoft Azure Cosmos DB have allowed us to meet our customers' expectations pretty easily with little barrier to entry."
"I like the scalability. There aren't any constraints for posting in the geolocation. I also like the SQL architecture."
"The latency and availability of Microsoft Azure Cosmos DB are fantastic."
 

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."
"However, when you need more volume or more registers, it becomes complicated because the performance adjustments and tuning are challenging."
"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."
"The query is a little complex. SQL server should have more options. But the query should be better."
"The price can always be lower, but currently, it's not a problem."
"Areas of improvement for Microsoft Azure Cosmos DB include indexing. While it makes data retrieval easier, it also increases costs."
"Slight enhancements in integration interfaces, expanded dashboard functionalities, and broader use-case support would be beneficial."
"A further simple application is required for Brazil."
"To show this in real time, we need a live connection that automatically updates in response to new records being inserted. This automated updating feature is lacking in Microsoft Azure Cosmos DB compared to Databricks."
"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."
"It would be ideal if we could integrate Cosmos DB with our Databricks. At this point, that's not possible."
 

Pricing and Cost Advice

Information not available
"Microsoft Azure Cosmos DB pricing is based on RUs. Reading 1 KB document costs one RU, whereas writing one document costs five RUs. Pricing for querying depends on the complexity of the query. If you increase the document size, it will automatically increase the RU cost."
"Cosmos DB is expensive compared to any virtual machine based on conventional RDBMS like MySQL or PostgreSQL."
"The price of Microsoft Azure Cosmos DB could be a bit lower."
"Microsoft Azure Cosmos DB is moderately priced, where it is neither expensive nor cheap."
"Cosmos DB is a PaaS, so there are no upfront costs for infrastructure. There are only subscriptions you pay for Azure and things like that. But it's a PaaS, so it's a subscription service. The license isn't perpetual, and the cost might seem expensive on its face, but you have to look at the upkeep for infrastructure and what you're saving."
"It is cost-effective. They offer two pricing models. One is the serverless model and the other one is the vCore model that allows provisioning the resources as necessary. For our pilot projects, we can utilize the serverless model, monitor the usage, and adjust resources as needed."
"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."
"Pricing is one of the solution's main features because it is based on usage, scales automatically, and is not too costly."
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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.
883,760 professionals have used our research since 2012.