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Faiss vs Microsoft Azure Cosmos DB comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Sep 29, 2024
 

Categories and Ranking

Faiss
Ranking in Vector Databases
3rd
Average Rating
8.0
Number of Reviews
2
Ranking in other categories
Open Source Databases (14th)
Microsoft Azure Cosmos DB
Ranking in Vector Databases
5th
Average Rating
8.2
Reviews Sentiment
7.3
Number of Reviews
78
Ranking in other categories
Database as a Service (DBaaS) (6th), NoSQL Databases (3rd), Managed NoSQL Databases (1st)
 

Featured Reviews

Vasu Bansal - PeerSpot reviewer
Provides quick query search and has a big database
I did not face any issues integrating Faiss with other tools. I would recommend the solution to other users. Faiss has facilitated my AI-driven project very well. I recommend that other users use it for their AI projects because it provides quick query search and has a big database. Overall, I rate the solution nine and a half out of ten.
Michael Calvin - PeerSpot reviewer
Easy to integrate, has a shallow learning curve, and scales dynamically
Azure Cosmos DB is quick to adopt with a shallow learning curve. The average user can be operational within hours or days, handling small to medium data volumes. However, optimizing for ultra-high throughput scenarios involves a steeper learning curve, requiring substantial knowledge to master Azure Cosmos DB. Nonetheless, most users can leverage it as their operational data store with minimal effort. Our platform boasts several extensive language model features, particularly around summarization capabilities. We use vector searching in Azure Cosmos DB to facilitate the retrieval of an augmented generation model with our LLM implementation. It's a standard RAG implementation using Azure Cosmos DB. Compared to other options, a key advantage of vector indexing in Azure Cosmos DB is the ability to query documents alongside vectors. This pinpoints the precise information required for RAG in our LLM solution, granting us greater flexibility than vector searching in other Azure services. We integrated the vector database with the Azure OpenAI service for our LLM solution. The Azure AI services were simple to integrate with the vector database. There was a slight learning curve, especially as we were on the private preview of vector searching. This led to some hiccups with our existing database configurations, specifically regarding continuous backup. We couldn't enable continuous backup and vector searching simultaneously. However, this was solely due to our participation in the preview, and I'm confident this issue won't persist in the general availability release. Azure Cosmos DB is fantastic for searching large amounts of data when the data is within a single partition. Over the last two weekends, we ingested over 400 gigabytes of data into our Azure Cosmos DB database and saw no change in querying performance compared to when our database was only 20 gigabytes in size. This is impressive and powerful, but the scope is limited to those partition queries. The first benefit we've seen is increased developer productivity. Azure Cosmos DB is an easy database to work with. Its schema-less nature allows us to iterate quickly on our platform, develop new features, and store the associated data in Azure. Developers find it easy to use, eliminating the need for object-relational mapping tools and other overhead. Geographic replication and the ability to scale geographically is another advantage. This is challenging with other databases, even other NoSQL databases, but Azure Cosmos DB makes it easy. Cost optimization is a major benefit as well. We've been able to run our platform at a fraction of the infrastructure cost our customers incur when integrating with us. This allows us to focus resources on feature development and platform building rather than infrastructure maintenance. Azure Cosmos DB helped reduce the total cost of ownership. We don't need DBAs, system administrators, or typical IT staff to run the infrastructure because we can use Azure Cosmos DB as a platform or a software-as-a-service data storage solution. This makes the total cost of ownership significantly lower than any comparable solution using relational databases or other NoSQL solutions like MongoDB. We enable auto-scaling on all of our Azure Cosmos DB resources, which helps us achieve cost optimizations.

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."
"Cosmos DB performs exceptionally well and has not caused any issues that necessitate adjustments in nodes for improved performance."
"Cosmos DB makes life easier because if we want to use Mongo-type data, or Cassandra-type data, or maybe even just a simple cable storage-type data, then graph, there are multiple ways to do this."
"What I like about Microsoft Azure Cosmos DB is that it's easy to do data ingestion and use the data in different applications. If you talk about business intelligence such as the Power BI tool, it's easy to connect because both are Microsoft products. With Microsoft Azure Cosmos DB, it's easy to connect and do data ingestion."
"The availability and latency of Azure Cosmos DB are excellent."
"The most valuable feature of Azure Cosmos DB is its scalability. That is the biggest reason I use Azure Cosmos DB."
"I would recommend Cosmos. It made our lives a lot easier. There's not a big learning curve in order to understand the structure and how to use it."
"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."
"The most valuable feature of Microsoft Azure Cosmos DB is its ability to handle concurrency and consistency."
 

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."
"A further simple application is required for Brazil."
"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."
"In Microsoft manufacturing, managers really need to know about the product."
"For streaming platforms, Azure Cosmos DB could improve efficiency in data storage. Indexing can also be better. Enhanced capabilities are necessary to manage increased data amounts more effectively during searches."
"One area of improvement for Cosmos database is the auto-scaling of RUs during high loads. It would be beneficial if the database could automatically scale resources rather than requiring manual adjustments."
"I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries."
"I do not have any specific suggestions for improvements at the moment. However, having more AI capabilities in the future would be beneficial."
"Azure Cosmos DB could be better for business intelligence and analytical queries."
 

Pricing and Cost Advice

"Faiss is an open-source solution."
"It is an open-source tool."
"Microsoft Azure Cosmos DB's licensing costs are monthly."
"Azure is a pay as you go subscription."
"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."
"When we've budgeted for our resources, it's one of the more expensive ones, but it's still not very expensive per month."
"From a startup point of view, it appears to be expensive. If I were to create my startup, it would not have the pricing appeal compared to the competition, such as Supabase. All those other databases are well-advertised by communities. I know there is a free tier with Azure Cosmos DB. It is just not well advertised."
"I would rate Cosmos DB's cost at seven out of ten, with ten being the highest."
"Its price is very good for the basic stuff. When you go to a more complicated use case, especially when you need replication and availability zones, it gets a little costly."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
19%
Financial Services Firm
13%
Manufacturing Company
9%
Educational Organization
8%
Computer Software Company
14%
Comms Service Provider
12%
Financial Services Firm
11%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Faiss?
I used Faiss as a basic database.
What needs improvement with Faiss?
I didn't know what algorithm was being learned to fetch my query. It would be beneficial if I could set a parameter and see different query mechanisms being run. I can then compare the results to s...
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?
The solution was a new product, so we didn't have a cost of ownership before. The cost has not surprised us. It's not been an issue. If we were doing multi-master replication globally, the cost wou...
What needs improvement with Microsoft Azure Cosmos DB?
Using it is easy. We are having trouble optimizing it. I'm not a technical person, so I couldn't explain why, but we're not getting the performance we were expecting. I'm sure it's probably an us p...
 

Comparisons

 

Also Known As

No data available
Microsoft Azure DocumentDB, MS Azure Cosmos DB
 

Learn More

Video not available
 

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 2024.
824,052 professionals have used our research since 2012.