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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
5th
Average Rating
9.4
Reviews Sentiment
5.3
Number of Reviews
3
Ranking in other categories
Open Source Databases (11th), AI Data Analysis (18th)
Supabase Vector
Ranking in Vector Databases
9th
Average Rating
8.4
Reviews Sentiment
5.3
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Vector Databases category, the mindshare of Qdrant is 6.9%, down from 7.9% compared to the previous year. The mindshare of Supabase Vector is 7.4%, up from 5.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Qdrant6.9%
Supabase Vector7.4%
Other85.7%
Vector Databases
 

Featured Reviews

CM
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 1-10 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.
AmritDash - PeerSpot reviewer
Automation Engineer at a educational organization with 11-50 employees
Unified course data has streamlined our AI study assistant and still needs better large-scale search
There can be compute spikes when we scale up, which we noticed during our intake season while processing millions of records. Massive similarity searches on a lot of vectors can spike the database CPU and potentially slow down API requests, so we had to move to a higher plan in Supabase for handling this during our intake season. There is no native hybrid search yet, which can combine keyword search and vector search. Supabase supports both, but combining them requires writing a custom Postgres function, while dedicated tools on other platforms allow you to do that out of the box. On some level, we face indexing complexity with Supabase Vector because although vectors expedite searches, we need to use indexes such as HNSW or IVF Flat. Tuning these indexes in Postgres requires advanced knowledge, and we needed a dedicated Supabase expert or to hire someone capable of understanding these complex queries and set this up for us, making it not a plug-and-play solution for a massive scale project with tens of millions of vectors. Vectors are stored in Postgres, and we can perform a lot of similarity searches on millions of vectors, which can spike database CPU and potentially slow down the app, but apart from that, everything seems positive.

Quotes from Members

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

Pros

"Qdrant has positively impacted my organization by consuming much less time than building systems through coding."
"Using Qdrant's hybrid search capability has improved my search results."
"Qdrant has reduced our response time to less than one second for our 128 KB token sizes, and we are satisfied with that performance."
"Supabase enables us to lower the skill floor while keeping the ceiling high."
"Supabase Vector has positively impacted our organization quite a lot, as we moved away from Pinecone to a unified platform where we store relational and vectorized data together, reducing automation times and eliminating the hassle of managing and maintaining two separate databases in sync."
"Supabase enables us to lower the skill floor while keeping the ceiling high."
"The platform's role-level security feature is quite effective for spatial data management."
"Supabase Vector rapidly increases the speed and efficiency with which I search through a database, helping with my data analysis tasks."
"Supabase Vector is easy to set up and cost-effective because the alternative is Firebase, which requires a credit card."
 

Cons

"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."
"I think there are still many Postgres features that can be developed further by the Supabase team."
"I think the support system can be better because after Supabase Vector stopped working in India, there is no support."
"I think there are still many Postgres features that can be developed further by the Supabase team."
"One area for the solution improvement is the inclusion of more sample code in various programming languages, particularly PHP."
"I notice that the schema visualizer can be improved. Additionally, the internal AI assistant powered by GPT can also be improved."
"There can be compute spikes when we scale up, which we noticed during our intake season while processing millions of records. Massive similarity searches on a lot of vectors can spike the database CPU and potentially slow down API requests, so we had to move to a higher plan in Supabase for handling this during our intake season."
 

Pricing and Cost Advice

Information not available
"The solution's cost is reasonable compared to other solutions."
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Comms Service Provider
11%
Computer Software Company
10%
Manufacturing Company
8%
Comms Service Provider
14%
Manufacturing Company
7%
Outsourcing Company
7%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise2
 

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?
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...
What is your primary use case for Qdrant?
Our use case for Qdrant is AI data analysis.
What needs improvement with Supabase Vector?
I think the support system can be better because after Supabase Vector stopped working in India, there is no support. Nobody knows how to deal with the database now. The naming structure is a littl...
What is your primary use case for Supabase Vector?
I'm using Supabase Vector for the Postgres part. I use their Postgres database as the main requirement for the product from my side. If I am building a small website or any product, I don't need to...
 

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 Qdrant vs. Supabase Vector and other solutions. Updated: April 2026.
893,221 professionals have used our research since 2012.