Faiss vs SingleStore comparison

Meta and SingleStore are both solutions in the Vector Databases category. Meta is ranked #5 with an average rating of 8.0, while SingleStore is ranked #15 with an average rating of 8.0. Meta holds a 5.1% mindshare in VD, compared to SingleStore’s 2.3% mindshare. Additionally, 100% of Meta users are willing to recommend the solution, compared to 100% of SingleStore users who would recommend it.

Faiss

Read 3 Faiss reviews

3,588 Views
3,265 Comparison Views

100% willing to recommend

SingleStore

Read 6 SingleStore reviews

2,326 Views
791 Comparison Views

100% willing to recommend

Faiss

SingleStore

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 5, 2025

SingleStore and Faiss operate in the realm of data processing and analytics. While SingleStore leads in pricing and support, Faiss holds an advantage in functionality due to its robust feature set.

Features: SingleStore offers high-speed transaction processing, scalability for real-time analytics, and complex query handling. Faiss provides efficient similarity search capabilities, which are ideal for AI and machine learning applications. These platforms differ in their primary functions, with SingleStore focused on operational efficiency and Faiss on specialized data search and retrieval tasks.

Ease of Deployment and Customer Service: SingleStore ensures seamless cloud integration and provides responsive support, highlighting its emphasis on easy setup and ongoing assistance. Faiss, while straightforward for those skilled in AI technologies, demands specific expertise for optimal deployment. SingleStore's priority on customer experience contrasts with Faiss's technical deployment focus.

Pricing and ROI: SingleStore offers competitive pricing aimed at maximizing ROI through high-performance analytics. Faiss necessitates a more significant initial investment in technical expertise, promising substantial ROI for organizations enhancing search operations within machine learning projects. SingleStore's strength is in cost-effective solutions, while Faiss offers value through advanced capabilities.

To learn more, read our detailed Faiss vs. SingleStore Report (Updated: December 2025).

Buyer's Guide

Faiss vs. SingleStore

December 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

Ranking in other categories

Open Source Databases (10th)

SingleStore

Ranking in Vector Databases

15th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Database as a Service (DBaaS) (11th)

Mindshare comparison

As of January 2026, in the Vector Databases category, the mindshare of Faiss is 5.1%, down from 12.3% compared to the previous year. The mindshare of SingleStore is 2.3%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Faiss	5.1%
SingleStore	2.3%
Other	92.6%

Vector Databases

Featured Reviews

Kalindu Sekarage

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.

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Vignesh KR

Solution Architect at Wipro Limited

An excellent choice for diverse data processing needs with exceptional in-memory capabilities, robust failover mechanisms, easy scalability and high performance

Scalability is its key strength. Adding servers for scalability is a straightforward process involving simply incorporating a few additional servers and recycling the cluster triggers automatic repartitioning and redistribution of data. For instance, if the initial database creation involved a hundred servers and later, four more servers are added, specific commands can be executed to increase the partitions to one hundred twenty. The data is then efficiently redistributed across the expanded partitions without the need for manual data movement, ensuring a seamless and efficient scalability process. In my current organization, approximately three projects involve the usage of SingleStore, with a team size ranging from ten to twenty individuals.

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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."

"The ability to store data in memory is a standout feature, enhanced by robust failover mechanisms."

"It's a distributed relational database, so it does not have a single server, it has multiple servers. Its architecture itself is fast because it has multiple nodes to distribute the workload and process large amounts of data."

"The product can automatically reinstall and reconfigure in case of a shutdown."

"The paramount advantage is the exceptional speed."

"MemSQL supports the MySQL protocol, and many functions are similar, so the learning curve is very short."

"The most valuable feature is the ability to create pipelines, streamline and extract data from the pipelines."

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 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."

"Poor key distribution can significantly impact performance, requiring a backward approach in design rather than adding tables incrementally."

"There should be more pipelines available because I think that if MemSQL can connect to other services, that would be great."

"It is not the optimal choice for direct data collection through queries, and it's more suited for aggregation tasks."

"We don't get good discounts in Pakistan."

"Having the ability to migrate servers using a single command would be extremely beneficial."

"For new customers, it's very tough to start. Their documentation isn't organized, and there's no online training available. SingleStore is working on it, but that's a major drawback."

Pricing and Cost Advice

"Faiss is an open-source solution."

"It is an open-source tool."

"They have two main options: cloud installation and bare-metal installation, each with different pricing models."

"The product's licensing is not expensive. It is comparable."

"Using it for analytical purposes can be cost-effective in the long run, especially in terms of infrastructure."

"SingleStore is a bit expensive."

"I would advise users to try the free 128GB version."

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Top Industries

By visitors reading reviews

Computer Software Company

15%

Financial Services Firm

14%

Manufacturing Company

Comms Service Provider

Financial Services Firm

30%

Computer Software Company

10%

Comms Service Provider

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	3

Questions from the Community

What do you like most about Faiss?

I used Faiss as a basic database.

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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...

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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...

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Product Reports

Buyer's Guide

Open Source Databases

January 2026

Download Faiss product report

Buyer's Guide

SingleStore

January 2026

Download SingleStore product report

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.

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

400+ customers including: 6sense, Adobe, Akamai, Ant Money, Arcules, CARFAX, Cigna, Cisco, Comcast, DELL, DBS Bank, Dentsu, DirectlyApply, EY, Factors.AI, Fathom Analytics, FirstEnergy, GE, Goldman Sachs, Heap, Hulu, IMAX, impact.com, Kroger, LG, LiveRamp, Lumana, Nvidia, OpenDialog, Outreach, Palo Alto Networks, PicPay, RBC, Samsung, SegMetrics, Siemens, SiteImprove, SiriusXM, SK Telecom, SKAI, SONY, STC, SunRun, TATA, Thorn, ZoomInfo.

Buyer's Guide

Faiss vs. SingleStore

December 2025

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