Faiss vs Microsoft Azure Cosmos DB comparison

Meta and Microsoft are both solutions in the Vector Databases category. Meta is ranked #5 with an average rating of 8.0, while Microsoft is ranked #1 with an average rating of 8.3. Meta holds a 5.1% mindshare in VD, compared to Microsoft’s 5.8% mindshare. Additionally, 100% of Meta users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Faiss

Read 3 Faiss reviews

3,588 Views
3,265 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

9,934 Views
4,272 Comparison Views

95% willing to recommend

Faiss

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 19, 2025

Microsoft Azure Cosmos DB and Faiss are strong contenders in the database and AI domain. Cosmos DB has an advantage in global distribution, while Faiss potentially outperforms it in specific AI applications due to its specialization.

Features:Microsoft Azure Cosmos DB provides globally distributed database services with multi-model and multi-API support, automatic scaling, and low latency across various geographies. Faiss offers fast similarity search, handles high-dimensional vectors, and is essential for machine learning tasks.

Ease of Deployment and Customer Service:Cosmos DB offers an easy cloud deployment with extensive documentation and integration, backed by Microsoft's support. Faiss relies on community support, requiring more technical expertise for integration, especially in larger systems.

Pricing and ROI:Microsoft Azure Cosmos DB's pricing varies based on throughput and storage, which can be costly with extensive use but offers scalability that enhances ROI globally. Faiss, as an open-source library, presents no direct cost, reducing setup expenses, although it requires a custom development investment.

To learn more, read our detailed Faiss vs. Microsoft Azure Cosmos DB Report (Updated: December 2025).

Buyer's Guide

Faiss vs. Microsoft Azure Cosmos DB

December 2025

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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

5th

Average Rating

8.0

Reviews Sentiment

3.3

Number of Reviews

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 January 2026, in the Vector Databases category, the mindshare of Faiss is 5.1%, down from 12.3% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 5.8%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Microsoft Azure Cosmos DB	5.8%
Faiss	5.1%
Other	89.1%

Vector Databases

Featured Reviews

Kalindu Sekarage

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.

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reviewer2724105

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.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The product has better performance and stability compared to one of its competitors."

"I used Faiss as a basic database."

"The best feature of Microsoft Azure Cosmos DB is API access, which makes it very easy to interact with the database without needing to write queries."

"Big data, along with data analysis, is one of the valuable features."

"Our customer is very satisfied with it."

"Some of the best features of Microsoft Azure Cosmos DB are that it could scale, and we could still use SQL language."

"Cosmos is a PaaS, so you don't need to worry about infrastructure and hosting. It has various APIs that allow it to integrate with other solutions. For example, we are using a MongoDB-compatible API for customers, which makes it easier for developers on the team who previously used MongoDB or are accustomed to the old document storage paradigm."

"Scaling the workloads is one of the key advantages of Cosmos, preventing the database from becoming a performance bottleneck."

"Overall, I would rate Microsoft Azure Cosmos DB a nine out of ten."

"The high speed of Azure Cosmos DB compared to other competitors is remarkable."

More Microsoft Azure Cosmos DB pros

Cons

"It would be beneficial if I could set a parameter and see different query mechanisms being run."

"It could be more accessible for handling larger data sets."

"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."

"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."

"Because there is no local way of doing things, Azure Cosmos DB will always be considered expensive."

"We had to go to forums to check if it was failing for everyone else. It was surprising that a large organization like Microsoft doesn't provide an official statement about the maintenance or issues that could impact our overall usage."

"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."

"Slight enhancements in integration interfaces, expanded dashboard functionalities, and broader use-case support would be beneficial."

"The query searching functionality has some complexities and could be more user-friendly. Improvements in this area would be very helpful."

"I hope they improve the service. Before last year, improvements on Cosmos DB were very slow."

"They can implement a better backup system or alert system on Microsoft's end. We do receive notices for regular maintenance or updates, but sudden issues create significant problems."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"It is an open-source tool."

"Faiss is an open-source solution."

"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."

"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."

"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."

"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."

"Its cost is transparent. Pricing depends on the transaction and data size, but overall, it is cheaper compared to hosting it on your corporate network due to other factors like power consumption."

"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 structure is quite flexible."

"You need to understand exactly the details of how the pricing works technically to stay within reasonable pricing."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

17%

Financial Services Firm

14%

Manufacturing Company

University

Legal Firm

13%

Financial Services Firm

11%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	21
Large Enterprise	58

Questions from the Community

What do you like most about Faiss?

I used Faiss as a basic database.

See all answers

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...

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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...

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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.

See all answers

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...

See all answers

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...

See all answers

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Product Reports

Buyer's Guide

Open Source Databases

December 2025

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Buyer's Guide

Microsoft Azure Cosmos DB

December 2025

Download Microsoft Azure Cosmos DB product report

Also Known As

No data available

Microsoft Azure DocumentDB, MS Azure Cosmos DB

Overview

Faiss is a powerful library for efficient similarity search and nearest neighbor retrieval in large-scale datasets. It is widely used in image and text processing, recommendation systems, and natural language processing.

Users appreciate its speed, scalability, and ability to handle high-dimensional data effectively. Faiss also offers easy integration and extensive support for different programming languages.

Its valuable features include efficient search capabilities, support for large-scale datasets, various similarity measures, easy integration, and comprehensive documentation and community support.

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

Buyer's Guide

Faiss vs. Microsoft Azure Cosmos DB

December 2025

Free Report: Faiss vs. Microsoft Azure Cosmos DB

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