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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
9th
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 May 2026, in the Managed NoSQL Databases category, the mindshare of Amazon DocumentDB is 6.5%, down from 9.6% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 15.7%, down from 16.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Managed NoSQL Databases Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Cosmos DB15.7%
Amazon DocumentDB6.5%
Other77.8%
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."
"Migrations are easy using this product."
"The product is fast and easy to use."
"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."
"Amazon DocumentDB is a simple solution."
"Efficient data retrieval with millisecond fetch times sets it apart from RDS."
"The solution is easy to use, and it is also easy to integrate with several things for database use cases."
"The efficiency of search capabilities is significant, particularly when it comes to the flexibility of conducting in-depth, almost recursive searches that are both efficient and cost-effective."
"It's highly scalable and supports consistency, security, and multiple security options."
"The latency and availability of Microsoft Azure Cosmos DB are fantastic."
"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."
"Overall, I think Microsoft Azure Cosmos DB works fine; I don't remember any case where our developers or our clients have been disappointed with it."
"The global synchronization feature of Azure Cosmos DB stands out as the most valuable for me."
"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."
 

Cons

"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."
"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."
"The technical support could be improved."
"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."
"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."
"It doesn't support all databases."
"The query is a little complex. SQL server should have more options. But the query should be better."
"Firstly, having a local development emulator or simulator for Azure Cosmos DB would be beneficial. It would be very handy to have a Docker container that developers can use locally."
"It should offer a simple user interface for querying Microsoft Azure Cosmos DB."
"A minor improvement would be enabling batch operations through the UI. Currently, to delete all documents in a collection, we must use an API, which some of my team finds inconvenient for admin tasks."
"The current data analytics of Cosmos DB is inefficient for large-scale queries due to its transactional design."
"The integration with other solutions needs to improve because Cosmos DB's interoperability is lacking in some scenarios. For example, I'm currently implementing Fabric. That involves migrating from environments without apps, processing data and users, and taking them to Fabric."
 

Pricing and Cost Advice

Information not available
"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."
"Right now, I have opted for the student subscription plan, for which Microsoft charges me around 100 USD. The pricing of the solution depends on the solution's usage."
"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."
"It is cost-efficient as long as you understand the right setup to optimize usage. Knowing the data needs of the organization and adjusting the Microsoft Azure Cosmos DB usage accordingly helps save costs, but if you don't know, you could end up spending more than necessary."
"Cosmos DB is cost-effective when starting but requires careful management."
"Because of the lack of understanding about RUs, the costs become unpredictable. It sometimes goes over the budget."
"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."
"The pricing for Cosmos DB has improved, particularly with the new pricing for Autoscale."
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
12%
Manufacturing Company
11%
Government
7%
Financial Services Firm
12%
Legal Firm
12%
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 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 needs improvement with Amazon DocumentDB?
We do not utilize Amazon DocumentDB's compatibility with MongoDB APIs because we do not have MongoDB in this client environment. There are current discussions about phasing out from AWS's Amazon Do...
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...
What is your primary use case for Microsoft Azure Cosmos DB?
We have a very large team of developers who develop a solution for our customers. In the part where they need some infrastructure on Microsoft Azure, we deploy entire environments of different type...
 

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: April 2026.
892,776 professionals have used our research since 2012.