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Elastic Search vs Faiss 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

Elastic Search
Ranking in Vector Databases
2nd
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
67
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st)
Faiss
Ranking in Vector Databases
5th
Average Rating
8.0
Reviews Sentiment
8.8
Number of Reviews
2
Ranking in other categories
Open Source Databases (13th)
 

Mindshare comparison

As of April 2025, in the Vector Databases category, the mindshare of Elastic Search is 5.8%, down from 7.1% compared to the previous year. The mindshare of Faiss is 9.2%, down from 17.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases
 

Featured Reviews

Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I find the solution to be fast."
"Dashboard is very customizable."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"The products comes with REST APIs."
"The special text processing features in this solution are very important for me."
"The most valuable feature of the solution is its utility and usefulness."
"I used Faiss as a basic database."
"The product has better performance and stability compared to one of its competitors."
 

Cons

"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff. They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"They could improve some of the platform's infrastructure management capabilities."
"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Better dashboards or a better configuration system would be very good."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"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."
 

Pricing and Cost Advice

"It can be expensive."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
"The price of Elastic Enterprise is very, very competitive."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"We are using the free version and intend to upgrade."
"The basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"we are using a licensed version of the product."
"It is an open-source tool."
"Faiss is an open-source solution."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
15%
Government
9%
Manufacturing Company
8%
Computer Software Company
19%
Financial Services Firm
13%
Manufacturing Company
9%
Educational Organization
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
I don't know about pricing. That is dealt with by the sales team and our account team. I was not involved with that.
What needs improvement with ELK Elasticsearch?
I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good. There is a maximum of 10,000 entries, so the limitation means that if...
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...
 

Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
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
Find out what your peers are saying about Elastic Search vs. Faiss and other solutions. Updated: March 2025.
845,040 professionals have used our research since 2012.