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Chroma 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

Chroma
Ranking in Vector Databases
10th
Average Rating
8.6
Reviews Sentiment
5.5
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Microsoft Azure Cosmos DB
Ranking in Vector 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), Managed NoSQL Databases (1st)
 

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of Chroma is 8.9%, down from 14.4% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 5.9%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
Microsoft Azure Cosmos DB5.9%
Chroma8.9%
Other85.2%
Vector Databases
 

Featured Reviews

Sameer Bhangale - PeerSpot reviewer
Leader, Data Science Practice at a computer software company with 5,001-10,000 employees
Used for RAG (Retrieval-augmented generation) and provides good documentation
If I have to deploy my application in a scalable environment with lots of data and users, I sometimes need to create multiple instances of my database or have a distributed database across different machines. Using Kubernetes, I can quickly increase the horizontal spread of Milvus because it is containerized and readily available. I don't have to do anything by myself. New users can go to Chroma's 'Get Started' page and follow it like a tutorial. Then, they will be ready to use the solution. Chroma has helped us reduce the overall project post production time. Overall, I rate the solution an eight out of ten.
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

"It's very easy to set up and runs easily."
"The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it."
"The solution is highly scalable."
"The feature I have found most valuable in Microsoft Azure Cosmos DB is its scalability and speed."
"The solution is stable."
"The fact that scalability can be achieved by simply configuring availability zones is very attractive."
"Microsoft Azure Cosmos DB offers the response times needed for advanced analytics applications."
"The ability to scale automatically is very valuable."
"Latency and availability are incredible."
"The biggest benefit it offers is scalability. It's easier to work with concurrency and updating data."
 

Cons

"I think Chroma doesn't have a ready-made containerized image available."
"The hybrid algorithm needs improvement."
"The pricing of the solution is an area with certain shortcomings."
"What is missing in Microsoft Azure Cosmos DB is definitely cold storage. We know it's coming, but that's currently what is missing—the possibility to park older data in a cold tier."
"Overall, it works very well and fits the purpose regardless of the target application. However, by default, there is a threshold to accommodate bulk or large requests. You have to monitor the Request Units. If you need more data for a particular query, you need to increase the Request Units."
"It would be ideal if we could integrate Cosmos DB with our Databricks. At this point, that's not possible."
"I had a challenging experience implementing the emulator with a Mac. I had to install the emulator in a Docker container because it is not natively compatible. A significant amount of time was spent researching how to enable HTTPS communication when connecting the container and the emulator."
"There were instances where the DB was not responding, and we lost some part of our business due to that."
"The topic of RU consumption needs better documentation. Now that Microsoft has partnered with different LLM organizations, such as OpenAI, a bot could guide us through different metrics present in Microsoft Azure Cosmos DB."
"A limitation in Azure Cosmos DB is the 2 MB document size. Developers need more systemic support in chaining multiple documents if more than 2 MB is required."
 

Pricing and Cost Advice

"The current version is an open-source."
"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."
"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."
"Because of the lack of understanding about RUs, the costs become unpredictable. It sometimes goes over the budget."
"If you are a small organization or startup building from scratch without the Microsoft Startup Founder Club support, it could be expensive."
"Pricing is mid- to high-end."
"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."
"The pricing for Microsoft Azure Cosmos DB is good. Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
10%
University
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 do you like most about Chroma?
The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it.
What needs improvement with Chroma?
The hybrid algorithm needs improvement.
What is your primary use case for Chroma?
We collect customer's feedback, and then we present it to the clients.
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

1. Google 2. Netflix 3. Amazon 4. Facebook 5. Microsoft 6. Apple 7. Twitter 8. Spotify 9. Adobe 10. Uber 11. Airbnb 12. LinkedIn 13. Pinterest 14. Snapchat 15. Dropbox 16. Salesforce 17. IBM 18. Intel 19. Oracle 20. Cisco 21. HP 22. Dell 23. Samsung 24. Sony 25. LG 26. Panasonic 27. Philips 28. Toshiba 29. Nokia 30. Motorola 31. Xiaomi 32. Huawei
TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify
Find out what your peers are saying about Chroma vs. Microsoft Azure Cosmos DB and other solutions. Updated: December 2025.
882,260 professionals have used our research since 2012.