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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
6th
Average Rating
8.0
Reviews Sentiment
3.3
Number of Reviews
3
Ranking in other categories
Open Source Databases (10th)
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 Faiss is 5.1%, down from 11.7% 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%
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."
"Azure Cosmos DB helped improve the quality of our search results."
"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."
"I like the scalability. There aren't any constraints for posting in the geolocation. I also like the SQL architecture."
"Microsoft Azure Cosmos DB is very fast."
"Cosmos DB performs exceptionally well and has not caused any issues that necessitate adjustments in nodes for improved performance."
"The ability to scale automatically is very valuable."
"Microsoft Azure Cosmos DB is easy to use and implement for application programmers."
 

Cons

"It could be more accessible for handling larger data sets."
"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."
"There should be a simpler way for data migration."
"There aren't any specific areas that need improvement, but if there were a way to achieve the right cosine similarity score without extensive testing, that would be very beneficial."
"Sometimes, the solution's access request takes time, which should be improved."
"One of our biggest pain points is the backup and restore functionality needs improvement."
"In the long run, there should be an addition of more features, especially because this space is evolving quickly. It all boils down to how many more features you are adding, how many integrations you are supporting, and how many more APIs you have that are standard APIs."
"Once you create a database, it calls the container, and then items show up. A better description and more guidance would help because the first time I created it, I didn't understand that a container is similar to a table in SQL."
"In Microsoft Azure Cosmos DB, I would suggest improvements in security."
"The pricing of the solution is an area with certain shortcomings."
 

Pricing and Cost Advice

"Faiss is an open-source solution."
"It is an open-source tool."
"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 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 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."
"The tool is not expensive."
"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."
"Everything could always be cheaper. I like that Cosmos DB allows us to auto-scale instead of pre-provisioning a certain capacity. It automatically scales to the demand, so we only pay for what we consume."
"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."
"Our experience with the pricing and setup cost is that it aligns with what we expect based on the pricing we see. However, I would absolutely like it to be less if possible."
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Top Industries

By visitors reading reviews
Computer Software Company
15%
Financial Services Firm
14%
Manufacturing Company
9%
Comms Service Provider
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 Enterprise21
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...
 

Comparisons

 

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: December 2025.
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