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Faiss vs Marqo comparison

 

Comparison Buyer's Guide

Executive Summary

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 Open Source Databases
13th
Ranking in Vector Databases
5th
Average Rating
8.0
Reviews Sentiment
3.3
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Marqo
Ranking in Open Source Databases
22nd
Ranking in Vector Databases
19th
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Open Source Databases category, the mindshare of Faiss is 3.8%, down from 3.9% compared to the previous year. The mindshare of Marqo is 0.3%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Open Source 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.
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
14%
Manufacturing Company
8%
University
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
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...
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Comparisons

 

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
1. Airbnb 2. Amazon 3. Apple 4. BMW 5. Cisco 6. CocaCola 7. Dell 8. Disney 9. Google 10.HP 11. IBM 12. Intel 13. JPMorgan Chase 14. Kraft Heinz 15. L'Oreal 16. McDonalds 17. Merck 18.Microsoft 19.Nike 20.Oracle 21.PG 22. PepsiCo 23.Procter and Gamble 24.Samsung 25. Shell  26.Sony 27. Toyota 28.Visa 29.Walmart 30.WeWork
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