Try our new research platform with insights from 80,000+ expert users

Qdrant vs Supabase Vector comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 1, 2026

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

Qdrant
Ranking in Vector Databases
4th
Average Rating
9.0
Reviews Sentiment
4.8
Number of Reviews
2
Ranking in other categories
Open Source Databases (11th), AI Data Analysis (17th)
Supabase Vector
Ranking in Vector Databases
11th
Average Rating
9.0
Reviews Sentiment
5.0
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of Qdrant is 7.6%, up from 7.6% compared to the previous year. The mindshare of Supabase Vector is 9.3%, up from 3.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Qdrant7.6%
Supabase Vector9.3%
Other83.1%
Vector Databases
 

Featured Reviews

reviewer2811174 - PeerSpot reviewer
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.
Kaustubh Sule - PeerSpot reviewer
Co-Founder • Full Stack Developer at Padhakoo
Easy to use, and there is no need to get involved in any tedious deployment process
If you are a business building a social media app, there will be thousands of users for every such app. Each user will have a post or something. When multiple users try to hit the like button on your post or try to comment on your post, each of them would be an API request, and Supabase Vector does not charge for them like. The API requests are kind of unlimited. If you compare Supabase Vector to any of the other services like Firebase, AWS, or Azure, all the tools charge per request. From a scalability standpoint, if you are a small-scale startup and you have around 1,00,000 or 2,00,000 users, then Supabase Vector is a perfect choice for you. I have never heard about any scalability issues in the product. Scalability-wise, I rate the solution a ten of ten.

Quotes from Members

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

Pros

"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%."
"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%."
"Supabase enables us to lower the skill floor while keeping the ceiling high."
"Supabase enables us to lower the skill floor while keeping the ceiling high."
"The tool is easy to use."
"The platform's role-level security feature is quite effective for spatial data management."
 

Cons

"Qdrant can be improved in several ways."
"Qdrant can be improved in several ways."
"The support for React Native CLI is an area with certain shortcomings where improvements are required."
"One area for the solution improvement is the inclusion of more sample code in various programming languages, particularly PHP."
"I think there are still many Postgres features that can be developed further by the Supabase team."
"I think there are still many Postgres features that can be developed further by the Supabase team."
 

Pricing and Cost Advice

Information not available
"The solution's cost is reasonable compared to other solutions."
"As per the product's regular pricing plans, the tools are available to users for 20 to 25 USD per month."
report
Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.
884,797 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Computer Software Company
12%
Financial Services Firm
11%
Comms Service Provider
11%
Manufacturing Company
8%
Comms Service Provider
14%
Computer Software Company
8%
Healthcare Company
6%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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.
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...
What is your primary use case for Qdrant?
My primary use cases for Qdrant are legal and educational.
What needs improvement with Supabase Vector?
I think there are still many Postgres features that can be developed further by the Supabase team.
What is your primary use case for Supabase Vector?
I am exploring Supabase for my project on UMKM.
 

Comparisons

 

Overview

 

Sample Customers

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
Information Not Available
Find out what your peers are saying about Microsoft, Elastic, Redis and others in Vector Databases. Updated: March 2026.
884,797 professionals have used our research since 2012.