Cassandra vs Faiss comparison

Apache and Meta are both solutions in the Vector Databases category. Apache is ranked #14 with an average rating of 8.1, while Meta is ranked #5 with an average rating of 8.0. Apache holds a 2.3% mindshare in VD, compared to Meta’s 5.1% mindshare. Additionally, 92% of Apache users are willing to recommend the solution, compared to 100% of Meta users who would recommend it.

Cassandra

Read 25 Cassandra reviews

2,135 Views
747 Comparison Views

92% willing to recommend

Faiss

Read 3 Faiss reviews

3,588 Views
3,265 Comparison Views

100% willing to recommend

Cassandra

Faiss

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Executive SummaryUpdated on Mar 5, 2025

Cassandra and Faiss compete in the field of database and search functionalities. Cassandra leads in scalability for extensive data management needs, whereas Faiss excels with efficient high-dimensional similarity searches.

Features: Cassandra focuses on its distributed database capabilities, supporting reliability and scalability. It handles large-scale data across multiple nodes efficiently. Faiss is known for its proficient indexing and search algorithms, allowing fast similarity searches in complex datasets. Cassandra encompasses broader data management needs, while Faiss specializes in rapid search functionalities.

Ease of Deployment and Customer Service: Faiss has a simpler deployment process, emphasizing integration with existing systems and offering specialized support for algorithmic queries. Cassandra, while requiring a more complex setup due to its distributed framework, provides extensive documentation and robust community support.

Pricing and ROI: Cassandra's initial setup cost is higher owing to its extensive infrastructure needs but promises a substantial long-term ROI through scalability and reliability. Faiss presents a lower setup cost with a rapid ROI attributed to its efficient high-speed search capabilities. The pricing differences highlight the initial expense versus long-term benefits with Faiss being cost-effective upfront and Cassandra offering greater advantages over time.

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

Buyer's Guide

Cassandra vs. Faiss

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

Cassandra

Ranking in Vector Databases

14th

Average Rating

8.0

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

NoSQL Databases (7th)

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)

Mindshare comparison

As of January 2026, in the Vector Databases category, the mindshare of Cassandra is 2.3%, up from 1.6% compared to the previous year. The mindshare of Faiss is 5.1%, down from 12.3% 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%
Cassandra	2.3%
Other	92.6%

Vector Databases

Featured Reviews

Monirul Islam Khan

Head, Data Integration & Management at a non-profit with 10,001+ employees

Has maintained secure document storage and efficient data distribution with peer-to-peer architecture

The functions or features in Cassandra that I have found most valuable are that it is a distributed system similar to Mongo. It's good enough for comparison with another SQL database, so it's smooth and organized for distributed database system. The peer-to-peer architecture in Cassandra is helpful for network decentralization, and I have already introduced that feature. Cassandra features in peer-to-peer as well as another monitoring, so basically, it's good enough for our service. The tunable consistency level in Cassandra is good, and we are using that feature already. In terms of built-in caching and lightweight transactions in Cassandra, the transaction level is good, and it's optimized, so there are no more issues in that database. Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there. Additionally, the database monitoring system or auditing system is well-comparable with other database systems, so we are actually happy to be using this Cassandra database.

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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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Quotes from Members

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

Pros

"Its retrieval is similar to an RDBMS, so our team finds it easy to adapt."

"The most valuable feature of Cassandra is its fast retrieval. Additionally, the solution can handle large amounts of data. It is the quickest application we use."

"The technical evaluation is very good."

"Overall, I would rate Cassandra as nine because of its fast writes, which really suit our use cases mostly."

"Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now."

"Some of the valued features of this solution are it has good performance and failover."

"We can add almost one million columns to the solution."

"Since I haven't had years of experience with it, it's still new to me. One valuable feature is its distribution, so I can run it partly in the cloud and part on-prem. That's a feature I'd like to use but haven't yet because we're trying to move to Azure. I don't know if or when that will happen. Ideally, we'd have it distributed over the cloud and on-prem simultaneously, so if something happens to our on-prem, we can keep going in the cloud, like a pay-as-you-go model with Azure."

More Cassandra pros

"The product has better performance and stability compared to one of its competitors."

"I used Faiss as a basic database."

Cons

"Interface is not user friendly."

"The solution doesn't have joins between tables so you need other tools for that."

"Cassandra could be more user-friendly like MongoDB."

"There could be more integration, and it could be more user-friendly."

"The solution is limited to a linear performance."

"The initial setup of Cassandra can be difficult in the configuration. There might be a need to have assistance. The implementation process can six months for connecting to certain databases."

"Cassandra can improve by adding more built-in tools. For example, if you want to do some maintenance activities in the cluster, we have to depend on third-party tools. Having these tools build-in would be e benefit."

"While Cassandra can handle NoSQL, I think there should be more flexibility for whole schema design when data is stored in wide columns. Additionally, I believe that eventual consistency should be enhanced."

More Cassandra cons

"It would be beneficial if I could set a parameter and see different query mechanisms being run."

"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."

Pricing and Cost Advice

"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."

"I use the tool's open-source version."

"We pay for a license."

"Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise."

"I don't have the specific numbers on pricing, but it was fairly priced."

"We are using the open-source version of Cassandra, the solution is free."

"Faiss is an open-source solution."

"It is an open-source tool."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

Retailer

Comms Service Provider

Computer Software Company

17%

Financial Services Firm

14%

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	1
Large Enterprise	14

No data available

Questions from the Community

What do you like most about Cassandra?

The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-ti...

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What is your experience regarding pricing and costs for Cassandra?

The pricing for Cassandra is a little bit high, so it would be better for our community services if they consider community pricing for any non-profit organization like an NGO or other things. It w...

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What needs improvement with Cassandra?

Regarding areas of improvement for Cassandra, currently, we are not facing significant issues. Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProx...

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What do you like most about Faiss?

I used Faiss as a basic database.

See all answers

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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Comparisons

ClickHouse vs Cassandra

Compared 14% of the time

MongoDB Enterprise Advanced vs Cassandra

Compared 13% of the time

Couchbase Enterprise vs Cassandra

Compared 10% of the time

ScyllaDB vs Cassandra

Compared 6% of the time

InfluxDB vs Cassandra

Compared 6% of the time

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Redis vs Faiss

Compared 10% of the time

Supabase Vector vs Faiss

Compared 8% of the time

MongoDB Enterprise Advanced vs Faiss

Compared 8% of the time

Milvus vs Faiss

Compared 8% of the time

Elastic Search vs Faiss

Compared 7% of the time

More Faiss Competitors

Product Reports

Buyer's Guide

Cassandra

December 2025

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Buyer's Guide

Open Source Databases

December 2025

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Overview

Cassandra is a distributed and scalable database management system used for real-time data processing.

It is highly valued for its ability to handle large amounts of data, scalability, high availability, fault tolerance, and flexible data model.

It is commonly used in finance, e-commerce, and social media industries.

Apache

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. Apple 2. Netflix 3. Facebook 4. Instagram 5. Twitter 6. eBay 7. Spotify 8. Uber 9. Airbnb 10. Adobe 11. Cisco 12. IBM 13. Microsoft 14. Yahoo 15. Reddit 16. Pinterest 17. Salesforce 18. LinkedIn 19. Hulu 20. Airbnb 21. Walmart 22. Target 23. Sony 24. Intel 25. Cisco 26. HP 27. Oracle 28. SAP 29. GE 30. Siemens 31. Volkswagen 32. Toyota

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

Buyer's Guide

Cassandra vs. Faiss

December 2025

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