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Faiss 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

Faiss
Ranking in Vector Databases
9th
Average Rating
8.0
Reviews Sentiment
3.3
Number of Reviews
3
Ranking in other categories
Open Source Databases (12th)
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 March 2026, in the Vector Databases category, the mindshare of Faiss is 5.1%, down from 10.6% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 5.9%, up from 2.1% 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%
Faiss5.1%
Other89.0%
Vector Databases
 

Featured Reviews

Kalindu Sekarage - PeerSpot reviewer
Senior Software Engineer
Integration improves accuracy and supports token-level embedding
The best features FAISS offers for my team include seamless integration with Colbert and the ability to use FAISS via the Ragatouille framework, which is tailor-made for using the Colbert model. Feature-wise, FAISS allows for more accurate result retrieval, and retrieval speed is also good when comparing the index size. Regarding features, I also emphasize that the usability of FAISS is very seamless, particularly its integration with Colbert and Ragatouille. FAISS has positively impacted my organization by helping us increase the accuracy of retrieval documents; when we store documents in token-level embedding, the accuracy will be high. Additionally, we do not need any external server to host FAISS, allowing us to integrate it with our backend framework, making it a very flexible framework.
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

"I used Faiss as a basic database."
"The product has better performance and stability compared to one of its competitors."
"I truly recommend Cosmos DB because it is a serverless product."
"Azure Cosmos DB helped improve the quality of our search results."
"Microsoft Azure Cosmos DB is easy to use and implement for application programmers."
"Microsoft Azure Cosmos DB offers the response times needed for advanced analytics applications."
"Microsoft Azure Cosmos DB's most valuable feature is latency."
"One of the nice features is the ability to auto-scale"
"The biggest benefit it offers is scalability. It's easier to work with concurrency and updating data."
"Microsoft Azure Cosmos DB is a Microsoft solution specifically, but we can develop with different developer kits for different databases."
 

Cons

"It would be beneficial if I could set a parameter and see different query mechanisms being run."
"One of the drawbacks of Faiss is that it works only in-memory. If it could provide separate persistent storage without relying on in-memory, it would reduce the overhead."
"It could be more accessible for handling larger data sets."
"The solution’s pricing could be improved."
"I don't think Cosmos DB has improved our organization. People are using it, but I'm not sure it's the best solution. For one, it's costly. Also, there are other issues with it. You cannot get all the records simultaneously. You can only get it in chunks of 1,500 maximum."
"It is not as easy to use as DynamoDB."
"There should be a simpler way for data migration."
"The main area of improvement is the cost, as the expense is high. Also, when writing processes into Cosmos, sometimes the threshold is met, which can be a problem if developers have not written the code properly, limiting calls to five thousand."
"Better documentation on how to integrate with other components would be helpful because I was struggling with this."
"The current data analytics of Cosmos DB is inefficient for large-scale queries due to its transactional design."
"The only area Microsoft Azure Cosmos DB can improve on is its documentation; while it is solid and very useful, enhancements in the indexing documentation would help users save costs and make it more cost-effective."
 

Pricing and Cost Advice

"It is an open-source tool."
"Faiss is an open-source solution."
"Microsoft Azure Cosmos DB's licensing costs are monthly."
"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."
"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."
"Microsoft Azure Cosmos DB is moderately priced, where it is neither expensive nor cheap."
"It seems to have helped significantly. We were using a different database system previously, and one of the reasons for acquiring Microsoft Azure Cosmos DB was cost."
"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."
"The customer had a high budget, but it turned out to be a little bit cheaper than what they expected. I am not sure how much they have spent so far, but they are satisfied with the pricing."
"The solution is very expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
13%
Manufacturing Company
9%
Educational Organization
9%
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 do you like most about Faiss?
I used Faiss as a basic database.
What is your experience regarding pricing and costs for Faiss?
I did not purchase FAISS through the AWS Marketplace because FAISS is an open-source product. My experience with pricing, setup cost, and licensing is straightforward, as there is no cost for acqui...
What needs improvement with Faiss?
I currently do not think there is anything to be improved based on our experience, as Faiss performs as we expected for our workflow. I would like to see improvement in the fact that FAISS currentl...
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. Facebook 2. Airbnb 3. Pinterest 4. Twitter 5. Microsoft 6. Uber 7. LinkedIn 8. Netflix 9. Spotify 10. Adobe 11. eBay 12. Dropbox 13. Yelp 14. Salesforce 15. IBM 16. Intel 17. Nvidia 18. Qualcomm 19. Samsung 20. Sony 21. Tencent 22. Alibaba 23. Baidu 24. JD.com 25. Rakuten 26. Zillow 27. Booking.com 28. Expedia 29. TripAdvisor 30. Rakuten 31. Rakuten Viber 32. Rakuten Ichiba
TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify
Find out what your peers are saying about Faiss vs. Microsoft Azure Cosmos DB and other solutions. Updated: February 2026.
883,044 professionals have used our research since 2012.