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Cube vs Qdrant comparison

 

Comparison Buyer's Guide

Executive Summary

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

Cube
Ranking in AI Data Analysis
34th
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
4
Ranking in other categories
Embedded BI (10th)
Qdrant
Ranking in AI Data Analysis
11th
Average Rating
9.0
Reviews Sentiment
5.7
Number of Reviews
6
Ranking in other categories
Open Source Databases (9th), Vector Databases (4th)
 

Mindshare comparison

As of July 2026, in the AI Data Analysis category, the mindshare of Cube is 0.3%. The mindshare of Qdrant is 0.4%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
Qdrant0.4%
Cube0.3%
Other99.3%
AI Data Analysis
 

Featured Reviews

Peter Jefferson - PeerSpot reviewer
Customer Success Manager at Unilever Inc.
Automated reporting has freed time for deeper analysis and improved budget and variance reviews
A specific example of how my team uses Cube in our day-to-day work is that above all, Cube has vastly enhanced our ability to get financial reporting done quickly and free up our time to really dig deep into various accounts. This has greatly improved the accuracy of our financial results beyond what you would even believe. The clean portal and organization help my team by making it easy to navigate and the data collected is very clean and managed in an understandable manner, hence making it very easy to make data-driven decisions. Regarding the features, customer service is great, customization of financial reports, ease of integration with other tools seamlessly, continuous system testing and upgrades, and easy creation of monthly and P&L variance analysis. Data import and export is smooth and efficient. Monthly reporting and analysis is easy to pull and update. The positive impact Cube has had on my organization includes additional time for analysis, less than budgeted spend, and more accurate financial results resulting in better decisions. The error rate has reduced from 40 to 50%. The reduction in errors has affected my team and the business overall by improving speed and efficiency for month-end close processes. Better consolidation of data for long-term trend analysis is evident, and easy P&L creation and variance analysis has been great.
Chirag Morajkar - PeerSpot reviewer
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
Building accurate no-code resume screeners has saved weeks in document search workflows
I see room for improvement in Qdrant based on what another platform called Weaviate offers. Qdrant provides an excellent vector database with a solid searching method. However, it could elevate its offering by integrating embedding features. Currently, for the workflow automation I build, I rely on other platforms for embedding, so incorporating this feature directly in Qdrant Cloud would eliminate the need to depend on external solutions. A pain point I have encountered was the inactive expiration of the cloud created for certain projects. If the cloud is not used for a week, it gets terminated, which is frustrating. I think increasing that inactivity window in the free tier would be beneficial, as I have faced limitations due to this seven-day inactivity rule, requiring me to reset up the cloud after its termination.

Quotes from Members

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

Pros

"Cube completes my tasks very easily and takes less time, allowing me to deliver any project in a timely manner to our clients."
"Implementation was super smooth, and within two weeks we were up and running and the metrics were exposed in our app."
"NPS improved to approximately eight out of ten for our feature, and internally ticket handling times decreased, allowing reallocation of resources to higher-impact projects."
"Qdrant has reduced our response time to less than one second for our 128 KB token sizes, and we are satisfied with that performance."
"Qdrant has positively impacted my organization by consuming much less time than building systems through coding."
"We saw a clear return on investment from Qdrant, particularly in the engineering time saved and the empowerment of team members to handle self-service tasks instead of reducing headcount."
"Using Qdrant's hybrid search capability has improved my search results."
"An accuracy boost was definitely observed from 45 to 50% using Faiss to around 85 to 95% using Qdrant, and the users are really happy as they are getting suggested really good schemes that would take a lot of time to find."
"Qdrant is an excellent vector database that anyone would want to use with RAG AI."
 

Cons

"Cube can be improved by enhancing data refresh over multiple tabs."
"There is no way to create a real template that is not exposed directly in the UI."
"Cube's interface can be challenging for non-technical users, needing clearer use-case examples to ease integration into workflows."
"I did not see any return on investment from Cube."
"Architectural complexity was a key friction point, as our primary database was set in Supabase, necessitating synchronization of two separate systems for user data, permissions, and states."
"One of the key limitations is that Qdrant does not have built-in role-based access control, and while being self-hosted is a benefit, it can also be improved."
"The file system lock in Qdrant prevents the API and scripts from hitting it directly, and to surpass this limitation, I have to run Qdrant client as a service, which incurs additional costs for running it continuously, so if something about that could be done, it would be really amazing."
"A pain point I have encountered was the inactive expiration of the cloud created for certain projects; if the cloud is not used for a week, it gets terminated, which is frustrating."
"The area for improvement in Qdrant is its clustering capability. While it has clustering functionality, it is not easy to set up, and not everyone can configure the clustering, so there is room for improvement in the clustering configuration."
"A lot of our work is agentic right now, and we have also segmented the content to be logical, so there's not a lot of vector search anymore."
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Top Industries

By visitors reading reviews
No data available
Comms Service Provider
11%
Financial Services Firm
10%
Manufacturing Company
10%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business8
 

Questions from the Community

What is your experience regarding pricing and costs for Cube?
The cost is around $1,500 per month. The exact number is not coming to my mind, but it is approximately $1,500 or $200 per month.
What needs improvement with Cube?
There is something that should be improved. We are providing metrics on email, and in the email industry we have both transactional emails and marketing emails. We have different models for these, ...
What is your primary use case for Cube?
We needed Cube in order to have a robust semantic layer on top of our ClickHouse database to avoid exposing our projection database directly in our app, and we needed to have sub-second latency met...
What is your experience regarding pricing and costs for Qdrant?
Licensing posed no issues, as Qdrant is open-source software with no upfront fees. Initially, the setup cost was low since we utilized a self-hosted model on a small cloud VM. However, as we added ...
What needs improvement with Qdrant?
While Qdrant is an exceptionally fast and efficient search engine within vector bases, our engineering team faced operational challenges during its adoption. Architectural complexity was a key fric...
What is your primary use case for Qdrant?
I have been using Qdrant for almost one and a half years. This was actually one of the first vector databases that we picked up in our organization. We started using the RAG modules to create a per...
 

Comparisons

No data available
 

Overview

 

Sample Customers

Information Not Available
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 Cube vs. Qdrant and other solutions. Updated: June 2026.
902,894 professionals have used our research since 2012.