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 Jan 25, 2026

Microsoft Azure Cosmos DB and Faiss compete in the database and search solution category. Microsoft Azure Cosmos DB appears to have an upper hand in terms of pricing transparency and support infrastructure.

Features: Microsoft Azure Cosmos DB offers global distribution, multi-model support, and comprehensive indexing capabilities which cater to scalable applications with low latency. Faiss focuses on efficient similarity search, clustering, and high-performance data operations that are ideal for resource-heavy tasks.

Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB integrates seamlessly with the Azure ecosystem, offering detailed documentation and extensive customer support, simplifying deployment for businesses. Faiss, as an open-source library, requires more technical engagement for deployment and features a community-supported model, adding flexibility for technical teams.

Pricing and ROI: Microsoft Azure Cosmos DB uses a pay-as-you-go model enhancing transparency and cost predictability, which offers potential ROI benefits for large applications. Faiss has minimal initial setup costs due to its open-source nature but may incur higher operational expenses dependent on technical expertise.

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.

Read full review

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 like the scalability. There aren't any constraints for posting in the geolocation. I also like the SQL architecture."

"It is integral to our business because it helps manage schema and metadata for all our documents and customers. The AI insights we glean based on Azure OpenAI also end up in Cosmos DB. We need a NoSQL store because the schema is dynamic and flexible, so Cosmos DB is a great fit. It has four nines or possibly five nines availability, excellent geo-distribution, and auto-scaling."

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

"The most valuable features include the global write capability, which allows customers to read and write across different regions simultaneously, enhancing performance and availability."

"One of the nice features is the ability to auto-scale"

"The solution is highly scalable."

"Microsoft Azure Cosmos DB is a Microsoft solution specifically, but we can develop with different developer kits for different databases."

"The benefits of Microsoft Azure Cosmos DB were immediate for us."

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."

"If we have a lot of data, doing a real-time vector search is a performance challenge because the search happens over a large dataset. It consumes more time."

"I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries."

"Areas of improvement for Microsoft Azure Cosmos DB include indexing. While it makes data retrieval easier, it also increases costs. If there's a better way to improve indexing at a lower cost, that would be really helpful, but that's the major point for now."

"The query searching functionality has some complexities and could be more user-friendly."

"I think Microsoft Azure Cosmos DB can be improved by providing continuous backup for multi-region rights. I believe it's available for non-multi-region rights, but there are many features that are locked behind continuous backup that I can't use because it's not enabled yet."

"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."

"One of our biggest pain points is the backup and restore functionality needs improvement."

"While Microsoft Azure Cosmos DB is generally easy to use, it has some limitations."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"It is an open-source tool."

"Faiss is an open-source solution."

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

"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."

"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."

"Pricing is one of the solution's main features because it is based on usage, scales automatically, and is not too costly."

"The tool is not expensive."

"Cosmos DB is a managed offering, so its cost is understandably higher."

"It is expensive. The moment you have high availability options and they are mixed with the type of multitenant architecture you use, the pricing is on the higher end."

"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

15%

Financial Services Firm

14%

Manufacturing Company

Comms Service Provider

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...

See all answers

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...

See all answers

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

January 2026

Download Faiss product report

Buyer's Guide

Microsoft Azure Cosmos DB

January 2026

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

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