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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

"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."
"Amazon DocumentDB is a simple solution."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Migrations are easy using this product."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"Microsoft Azure Cosmos DB is a Microsoft solution specifically, but we can develop with different developer kits for different databases."
"The most valuable features of Microsoft Azure Cosmos DB were the general infrastructure, ease to use, and interface."
"The standout features are its ability to do data compression easily and the ability to scale horizontally."
"It is integral to our business because it helps manage schema and metadata for all our documents and customers. The AI insights we glean based on Azure OpenAI also end up in Cosmos DB. We need a NoSQL store because the schema is dynamic and flexible, so Cosmos DB is a great fit. It has four nines or possibly five nines availability, excellent geo-distribution, and auto-scaling."
"The latency and availability of Microsoft Azure Cosmos DB are fantastic."
"The feature I have found most valuable in Microsoft Azure Cosmos DB is its scalability and speed."
"For example, we have people spread across multiple locations; if they update data in Australia, we can access it in another location within a fraction of a second."
"The graphical representation of data is the most valuable feature of the solution."
 

Cons

"There's a bit of a learning curve at the beginning."
"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."
"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."
"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."
"One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document."
"The query is a little complex. SQL server should have more options. But the query should be better."
"I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries."
"There is room for improvement in terms of stability."
"Cosmos DB should continue evolving in AI features. We expect Cosmos DB to lead on that. There is potential for improved security features, which is important for data storage, especially for Dell Technologies. We must ensure data security remains the top priority."
"Because there is no local way of doing things, Azure Cosmos DB will always be considered expensive."
"The UI needs enhancement. Unlike SQL, Cosmos DB's UI is not as straightforward, making it a bit challenging to use efficiently."
"It doesn't support all databases."
 

Pricing and Cost Advice

Information not available
"Most customers like the flexibility of the pricing model, and it has not been an issue. They can start small, and the cost grows with adoption, allowing efficient management of the budget. Its pricing model has not been a concern at all for any of our customers. They understand it. It is simple enough to understand. Oftentimes, it is hard to forecast the RUs, but, in general, it has been fine."
"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."
"Its pricing is higher compared to solutions like Aerospike. However, it is justified because of the out-of-the-box features that are provided. The availability and resiliency that we have make it worth the price."
"Microsoft provides fair pricing."
"Its price is in the middle, neither too low nor too high."
"Azure Cosmos DB is generally a costly resource compared to other Azure resources. It comes with a high cost. We have reserved one thousand RUs. Free usage is also limited."
"With heavy use, like a large-scale IoT implementation, you could easily hit a quarter of a million dollars a month in Azure charges if Cosmos DB is a big part of it."
"Cost isn’t a big hurdle for us right now. The solution is not costly."
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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.