Cassandra vs Qdrant comparison

Apache and Qdrant are both solutions in the Vector Databases category. Apache is ranked #14 with an average rating of 8.1, while Qdrant is ranked #4 with an average rating of 10.0. Apache holds a 2.6% mindshare in VD, compared to Qdrant’s 7.6% mindshare. Additionally, 92% of Apache users are willing to recommend the solution, compared to 100% of Qdrant users who would recommend it.

Cassandra

Read 25 Cassandra reviews

2,478 Views
942 Comparison Views

92% willing to recommend

Qdrant

Read 2 Qdrant reviews

3,083 Views
2,528 Comparison Views

100% willing to recommend

Cassandra

Qdrant

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Cassandra and Qdrant based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Elastic, Redis and others in Vector Databases.

To learn more, read our detailed Vector Databases Report (Updated: March 2026).

Buyer's Guide

Vector Databases

March 2026

Download the complete report

Helped 884,873 peers since 2012

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)

Qdrant

Ranking in Vector Databases

4th

Average Rating

9.0

Reviews Sentiment

4.8

Number of Reviews

Ranking in other categories

Open Source Databases (11th), AI Data Analysis (17th)

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of Cassandra is 2.6%, up from 1.7% compared to the previous year. The mindshare of Qdrant is 7.6%, up from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
Qdrant	7.6%
Cassandra	2.6%
Other	89.8%

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.

Read full review

reviewer2811174

AI Developer at a tech services company with 11-50 employees

Vector search has transformed support workflows and drives faster, more accurate responses

Qdrant can be improved in several ways. A dashboard or UI for re-indexing large collections without downtime and performance degradation would be valuable. The ecosystem around managed backups and cross-region replication could be more seamless for global deployments. Built-in analytics or observability tooling, such as a query performance dashboard and index health monitor, would reduce reliance on external tools. Tighter integration with popular orchestration frameworks like LangChain and LlamaIndex out of the box and more intuitive documentation would be very helpful. Developers need parameters for advanced fine-tuning, such as HNSW settings, and documentation could be clearer. For people without much experience in AI frameworks or vector databases, easier documentation would be helpful. At least the setup part could be simpler. These are some negatives I am observing.

Read full review

Quotes from Members

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

Pros

"A consistent solution."

"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."

"Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there."

"The most valuable features of Cassandra are its scaling capabilities and its non-SQL nature capabilities."

"Our primary use case for the solution is testing."

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

"I am getting much better performance than relational databases."

"The time series data was one of the best features along with auto publishing."

More Cassandra pros

"Due to its quantization ability, we were able to store the same amount of data in less space, which reduced our cloud bills by 30%."

"Using Qdrant's hybrid search capability has improved my search results."

"Due to its quantization ability, we were able to store the same amount of data in less space, which reduced our cloud bills by 30%."

Cons

"Doesn't support a solution that can give aggregation."

"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."

"The secondary index in Cassandra was a bit problematic and could be improved."

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

"Batching bulk data can cause performance issues."

"Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProxy, which should better handle consumption for high-level concurrency."

"The solution is not easy to use because it is a big database and you have to learn the interface. This is the case though in most of these solutions."

"It can be difficult to analyze what's going on inside of the database relative to other databases. It can also be difficult to troubleshoot sometimes."

More Cassandra cons

"Qdrant can be improved in several ways."

Pricing and Cost Advice

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

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

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

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

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

"We pay for a license."

Information not available

See which vendors are best for you

Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.

See recommendations

884,873 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

Comms Service Provider

Retailer

Computer Software Company

12%

Financial Services Firm

11%

Comms Service Provider

11%

Manufacturing Company

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...

See all answers

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...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Qdrant?

Using Qdrant is free. We house it and have a VM where we just installed it on the VM.

See all answers

What needs improvement with Qdrant?

I should check if real-time data updates in Qdrant have helped improve my models, as I don't even know they have that feature. A lot of our work is agentic right now, and we have also segmented the...

See all answers

What is your primary use case for Qdrant?

My primary use cases for Qdrant are legal and educational.

See all answers

Comparisons

ClickHouse vs Cassandra

Compared 10% of the time

MongoDB Enterprise Advanced vs Cassandra

Compared 10% of the time

Couchbase Enterprise vs Cassandra

Compared 7% of the time

ScyllaDB vs Cassandra

Compared 5% of the time

Oracle NoSQL vs Cassandra

Compared 4% of the time

More Cassandra Competitors

Supabase Vector vs Qdrant

Compared 20% of the time

Microsoft Azure Cosmos DB vs Qdrant

Compared 7% of the time

LanceDB vs Qdrant

Compared 7% of the time

MongoDB Enterprise Advanced vs Qdrant

Compared 6% of the time

PostgreSQL vs Qdrant

Compared 6% of the time

More Qdrant Competitors

Product Reports

Buyer's Guide

Cassandra

March 2026

Download Cassandra product report

Buyer's Guide

Open Source Databases

February 2026

Download Qdrant product report

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

Qdrant is a powerful tool for efficiently organizing and searching large volumes of data. It is particularly useful for tasks such as data indexing, similarity search, and recommendation systems.

With fast and accurate results, it is suitable for various applications including e-commerce, content management, and data analysis. Users appreciate Qdrant's efficient search capabilities, high performance, and ease of use.

Its quick and accurate retrieval of relevant information allows for easy navigation and analysis of large datasets.

The intuitive interface and straightforward setup process make it accessible to users with varying levels of technical expertise.

Qdrant

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. 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. Nike20. Oracle 21. PG 22. PepsiCo 23. Procter and Gamble 24. Samsung 25. Shell 26. Sony 27. Toyota 28. Visa 29. Walmart 30. WeWork

Find out what your peers are saying about Microsoft, Elastic, Redis and others in Vector Databases. Updated: March 2026.

DOWNLOAD NOW

884,873 professionals have used our research since 2012.

See our list of best Vector Databases vendors.

We monitor all Vector Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.