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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 8.2. Meta holds a 5.6% mindshare in VD, compared to Microsoft’s 4.8% 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
  • 3,536 Views
  • 3,288 Comparison Views
100% willing to recommend
Microsoft Azure Cosmos DB
Read 102 Microsoft Azure Cosmos DB reviews
  • 7,050 Views
  • 2,750 Comparison Views
95% willing to recommend
 

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 13, 2025

Microsoft Azure Cosmos DB and Faiss compete in the domain of data management and retrieval, with Azure Cosmos DB offering comprehensive global database solutions and Faiss providing efficient local similarity search capabilities. In terms of scalability and support, Microsoft Azure Cosmos DB has a clearer edge with its extensive service offerings, while Faiss shines in performance for niche applications.

Features: Microsoft Azure Cosmos DB offers global distribution, multi-model data support, and real-time processing. Faiss provides rapid similarity search, efficient for image and vector data, and is suited for high-speed retrieval tasks in machine learning environments. Azure Cosmos DB integrates service support for various data models, whereas Faiss is tailored for performance-focused tasks.

Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB has a straightforward deployment process globally with extensive customer support options. Faiss suits localized deployment but requires technical expertise in machine learning and indexing. Azure Cosmos DB presents clearer pathways for services, while Faiss demands specialized knowledge but excels in search efficiency once properly set up.

Pricing and ROI: Microsoft Azure Cosmos DB's pricing model emphasizes its scalability and global reach, often leading to higher costs but delivering significant returns for businesses utilizing these features. Faiss is typically free with a need for technical setup, offering high ROI for specialized vector search applications. Azure Cosmos DB is structured for scalable investments, whereas Faiss is cost-effective for specific performance needs.

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Buyer's Guide
Faiss vs. Microsoft Azure Cosmos DB
July 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
3
Ranking in other categories
Open Source Databases (12th)
Microsoft Azure Cosmos DB
Ranking in Vector Databases
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
102
Ranking in other categories
Database as a Service (DBaaS) (5th), NoSQL Databases (2nd), Managed NoSQL Databases (1st)
 

Mindshare comparison

As of September 2025, in the Vector Databases category, the mindshare of Faiss is 5.6%, down from 14.7% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 4.8%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
Microsoft Azure Cosmos DB4.8%
Faiss5.6%
Other89.6%
Vector Databases
 

Featured Reviews

Kalindu Sekarage - PeerSpot reviewer
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.
Read full review
MichaelJohn - PeerSpot reviewer
Very efficient for application-facing scenarios
There are several areas for improvement. Firstly, having a local development emulator or simulator for Azure Cosmos DB would be beneficial. It would be very handy to have a Docker container that developers can use locally. Although, I know there is a free tier and so on and so forth, having a local environment would be nice. For example, SQL Server is very portable. You can even install it on your machine. That is the number one thing that is missing in Azure Cosmos DB. The second improvement area is the IDE of choice. That means how you interact with Azure Cosmos DB. For example, with SQL Server, you have SQL Server Management Studio. I know there is a little bit of support for Azure Cosmos DB in Azure Data Studio, but it is not heavily advertised or it does not feel like first-class citizen support. Developer experience or developer tooling is missing in terms of interacting with the database. Better developer tools or an IDE for interacting with Azure Cosmos DB would enhance the developer experience. Lastly, there is some mixed messaging about what Azure Cosmos DB is, given its multiple APIs. There are so many Azure Cosmos DB APIs available. There is NoSQL. There are MongoDB, Gremlin, and others. There is still some mixed messaging for others who are new to Azure Cosmos DB about what Azure Cosmos DB is. Is this like MongoDB, but then there is also MongoDB in Azure Cosmos DB? I know it well, and I know that the default one is just NoSQL, but others I have interacted with over the last ten years or so get confused.
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

"The product has better performance and stability compared to one of its competitors."
"I used Faiss as a basic database."
"Its wide support to the ecosystem is valuable. We can use this database with a lot of use cases, and that's one of the reasons why we prefer it. We have a lot of vendors, databases, and use cases, and wherever possible, we are trying to standardize databases. It is also secure."
"Cosmos DB has helped our organization handle large amounts of data."
"The most valuable features include the global write capability, which allows customers to read and write across different regions simultaneously, enhancing performance and availability."
"For example, we have people spread across multiple locations; if they update data in Australia, we can access it in another location within a fraction of a second."
"The solution's read capacity and write access functions are very fast so users don't have to wait when fetching or displaying data on a screen."
"The solution is extremely user-friendly and easy to navigate."
"Cosmos DB has helped us by providing faster response times for everything, which significantly improved our search results quality."
"The best feature about Microsoft Azure Cosmos DB is its interface, which is awesome for accessing data."
More Microsoft Azure Cosmos DB pros
 

Cons

"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 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."
"There were instances where the DB was not responding, and we lost some part of our business due to that."
"The query searching functionality has some complexities and could be more user-friendly. Improvements in this area would be very helpful."
"The built-in integration of the solution is tight."
"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 are no particular factors that need improvement. There is a little bit of a learning curve with scaling workloads, but it works smoothly."
"The size of the continuation token in Azure Cosmos DB should be static rather than increasing with more data, as it can lead to application crashes. They should use a static key size."
"Continuing to educate customers on how they can take better advantage of Microsoft Azure Cosmos DB without having to completely rewrite their entire application paradigm would be beneficial."
"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."
More Microsoft Azure Cosmos DB cons
 

Pricing and Cost Advice

"It is an open-source tool."
"Faiss is an open-source solution."
"Pricing is one of the solution's main features because it is based on usage, scales automatically, and is not too costly."
"With heavy use, like a large-scale IoT implementation, you could easily hit a quarter of a million dollars a month in Azure charges if Cosmos DB is a big part of it."
"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."
"Pricing is mid- to high-end."
"You need to understand exactly the details of how the pricing works technically to stay within reasonable pricing."
"The pricing and licensing model was initially difficult to understand, but as soon as I learned what was going on and how it was priced, it was pretty easy."
"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-effective. They offer two pricing models. One is the serverless model and the other one is the vCore model that allows provisioning the resources as necessary. For our pilot projects, we can utilize the serverless model, monitor the usage, and adjust resources as needed."
More Microsoft Azure Cosmos DB pricing and cost advice
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
14%
Manufacturing Company
8%
Educational Organization
8%
Legal Firm
13%
Financial Services Firm
10%
Comms Service Provider
10%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
 

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?
The pricing for Microsoft Azure Cosmos DB is good, but there is a developer factor to consider. It could be economical or expensive depending on usage. Guidance about query consumption of Request U...
See all answers
What needs improvement with Microsoft Azure Cosmos DB?
In terms of improvement for Microsoft Azure Cosmos DB, while it eliminates the burden of managing database infrastructure, we realized it might not be possible to use various models simultaneously ...
See all answers
 

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Product Reports

Buyer's Guide
Open Source Databases
August 2025
Faiss reportDownload Faiss product report
Buyer's Guide
Microsoft Azure Cosmos DB
August 2025
Microsoft Azure Cosmos DB reportDownload 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.

Meta

Microsoft Azure Cosmos DB is a globally distributed, multi-model database service providing scalability, user-friendliness, and seamless integration, suitable for managing large volumes of structured and unstructured data across diverse applications.

Azure Cosmos DB is renowned for its scalability, stability, and ease of integration, offering robust support for multiple data models and APIs. Its capacity for handling unstructured data efficiently and providing real-time analytics makes it ideal for applications requiring high performance and global distribution. With features like automatic failover and integration with Microsoft products, users benefit from cost optimization and secure data handling. Enhancement opportunities include simplifying queries, improving documentation, and expanding backup and analytics functionalities.

What are the most important features of Microsoft Azure Cosmos DB?
  • Scalability and Autoscaling: Efficiently handles growing data and user demands.
  • Multi-Model Support: Adapts to different data models seamlessly.
  • Global Distribution: Provides low-latency access across multiple regions.
  • Automatic Failover: Ensures high availability and reliability.
  • Integration with Microsoft Products: Offers seamless connectivity with Azure services.
What benefits should users look for in Microsoft Azure Cosmos DB reviews?
  • Performance and Speed: Exceptionally fast processing for real-time data analytics.
  • Cost Optimization: Tools for managing expenses effectively.
  • Secure Data Handling: Implements strong data security measures.
  • Flexible Data Ingestion: Supports diverse data ingestion methods.

Azure Cosmos DB is frequently used in sectors like web, mobile, IoT, and analytics. It supports applications as a key-value store, processes real-time data, and enables global scalability with low-latency access. Its big data management capabilities and integration with Azure services enhance its utility across industries.

Microsoft
 

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
July 2025
Free Report: Faiss vs. Microsoft Azure Cosmos DB
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