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Faiss vs Pinecone comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 5, 2025

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
4th
Average Rating
8.0
Reviews Sentiment
3.3
Number of Reviews
3
Ranking in other categories
Open Source Databases (11th)
Pinecone
Ranking in Vector Databases
6th
Average Rating
8.4
Reviews Sentiment
6.5
Number of Reviews
9
Ranking in other categories
AI Data Analysis (12th), AI Content Creation (5th)
 

Mindshare comparison

As of December 2025, in the Vector Databases category, the mindshare of Faiss is 5.2%, down from 12.7% compared to the previous year. The mindshare of Pinecone is 7.3%, down from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
Faiss5.2%
Pinecone7.3%
Other87.5%
Vector Databases
 

Featured Reviews

Kalindu Sekarage - PeerSpot reviewer
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.
Pradeep Gudipati - PeerSpot reviewer
Chief Technology Advisor at Kovaad technologies Pvt Ltd
Faced challenges with metadata filtering but have achieved reliable long-term memory for chat applications
We were looking at multiple options for a vector database, and we found Pinecone to be the easiest to integrate into our solution. Plus, it has a very generous free tier, which helps us as a startup. The best features Pinecone offers are quick setup and good indexing for us. The retrieval mechanisms are fast, and the integration with Python as with JavaScript and TypeScript libraries that Pinecone provides are very robust. Authentication is also very good. The namespaces feature allows us to break down or store data for each user separately, reducing interference and maintaining privacy as an important feature. Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database. We are seeing that the trainees getting trained on the platform are more satisfied with the results or messages generated by AI.

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."
"We chose Pinecone because it covers most of the use cases."
"The semantic search capability is very good."
"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."
"Pinecone's integration with AWS was seamless."
"Pinecone has positively impacted my organization by helping people in needle-in-a-haystack situations, as previously they had to grind through PDF documents, PowerPoint documents, and websites, but now with Pinecone, they can ask questions and receive references to documents along with the page numbers where that information exists, so they can use it as a reference or backtrack, especially for things such as FDA approvals where they can quote the exact page number from PDF documents, eliminating hallucination and providing real-time data that relies on an external vector database with enough guardrails to ensure it won't provide information not in the vector database, confining it to the information present in the indexes."
"The product's setup phase was easy."
"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."
"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."
 

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."
"If Pinecone gave us RAG as a service, we'd be more than happy to use that."
"Pinecone is good as it is, but had it been on AWS infrastructure, we wouldn't experience some network lags because it's outside AWS."
"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."
"The tool does not confirm whether a file is deleted or not."
"I want to suggest that Pinecone requires a login and API key, but I would prefer not to have a login system and to use the environment directly."
"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."
"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."
"Onboarding could be better and smoother."
 

Pricing and Cost Advice

"It is an open-source tool."
"Faiss is an open-source solution."
"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid version."
"Pinecone is not cheap; it's actually quite expensive. We find that using Pinecone can raise our budget significantly. On the other hand, using open-source options is more budget-friendly."
"I have experience with the tool's free version."
"The solution is relatively cheaper than other vector DBs in the market."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
14%
Manufacturing Company
9%
University
8%
Computer Software Company
15%
Financial Services Firm
8%
Manufacturing Company
7%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise3
 

Questions from the Community

What do you like most about Faiss?
I used Faiss as a basic database.
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...
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...
What do you like most about Pinecone?
We chose Pinecone because it covers most of the use cases.
What needs improvement with Pinecone?
I give Pinecone a nine out of ten because I hope it provides an end-to-end agentic solution, but currently, it doesn't have those agentic capabilities, meaning I have to create a Streamlit applicat...
What is your primary use case for Pinecone?
My main use case for Pinecone is creating vector indexes for GenAI applications. A specific example of how I use Pinecone in one of my projects is utilizing a RAG pipeline where I take text from PD...
 

Comparisons

 

Overview

 

Sample Customers

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1. Airbnb 2. DoorDash 3. Instacart 4. Lyft 5. Pinterest 6. Reddit 7. Slack 8. Snapchat 9. Spotify 10. TikTok 11. Twitter 12. Uber 13. Zoom 14. Adobe 15. Amazon 16. Apple 17. Facebook 18. Google 19. IBM 20. Microsoft 21. Netflix 22. Salesforce 23. Shopify 24. Square 25. Tesla 26. TikTok 27. Twitch 28. Uber Eats 29. WhatsApp 30. Yelp 31. Zillow 32. Zynga
Find out what your peers are saying about Faiss vs. Pinecone and other solutions. Updated: December 2025.
879,259 professionals have used our research since 2012.