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Supabase Vector vs Vespa 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

Supabase Vector
Ranking in Vector Databases
6th
Average Rating
8.6
Reviews Sentiment
5.4
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Vespa
Ranking in Vector Databases
20th
Average Rating
7.8
Reviews Sentiment
5.3
Number of Reviews
4
Ranking in other categories
Open Source Databases (20th)
 

Mindshare comparison

As of June 2026, in the Vector Databases category, the mindshare of Supabase Vector is 6.3%, down from 7.0% compared to the previous year. The mindshare of Vespa is 2.3%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Supabase Vector6.3%
Vespa2.3%
Other91.4%
Vector Databases
 

Featured Reviews

Alberto Hidalgo - PeerSpot reviewer
Co-Founder
Vector search has reduced duplicate citizen proposals and empowers richer democratic participation
I had problems integrating the vector directly into Supabase, so I had to use Google Vertex to generate the embeddings and the information I needed in the database. It would be nice if all of this could be integrated all in one place with Supabase. I would prefer not to have to use a different or external tool to create these embeddings. It would be nice to have everything integrated in the same way. Apart from that, I think that is one of the cons I found, but it is basic. That was my main concern in that regard. My advice for others looking into using Supabase Vector is to take into account how you are going to create the embeddings, as it is not an option implemented straight away in Supabase. You will need to handle the embeddings with an external tool, so make sure to consider how these integrations are going to be made.
Ganaraj Amakrishna - PeerSpot reviewer
Lead Technical Architect at Zoro UK
Vector search has improved e‑commerce relevance but setup and learning curve still need work
Vespa definitely had its own set of challenges. It was really hard to get into initially, especially when I started implementing it in 2024 along with one junior employee, and the lack of documentation made it difficult. I aimed for an implementation with ColBERT, a sparse embedding mechanism, which I believed would fit well for e-commerce. We went through iterations during A/B testing because the initial set did not work as expected, which extended the process to about one and a half years. Vespa has a considerable learning curve, making it challenging for most people to get into, and it is also expensive, which can deter startups or those with smaller budgets from using it. Community support was decent, and we turned to it for clarifications. However, substantial improvements in documentation are necessary, especially more examples for handling DSL effectively. Having a runtime testing feature would greatly facilitate quick iterations.

Quotes from Members

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

Pros

"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."
"We completed what we initially estimated as a fifteen-day job in just three days, thanks to the Supabase dashboards and triggers."
"Supabase Vector is easy to set up and cost-effective because the alternative is Firebase, which requires a credit card."
"Supabase Vector has positively impacted our organization as it is very convenient since our business databases are already hosted in Supabase, making integration easy."
"Supabase Vector rapidly increases the speed and efficiency with which I search through a database, helping with my data analysis tasks."
"Supabase Vector positively impacts my organization by reducing the cost of the LLMs."
"The most valuable part using Supabase Vector is how complex things I was able to build and deploy in a short period of time."
"Vespa is very good and it improves our product, and we got more clients."
"While conducting A/B testing, Vespa seemed to be performing slightly better than Elasticsearch, especially in search relevancy within live production systems, and its performance was decent."
"The most outstanding features and characteristics of Vespa include an architecture that lets you focus on implementing features, the function that automatically manages sharding and shards is excellent, and the flexibility of the server cluster and infrastructure architecture is outstanding."
"The best feature to me is the LTR feature, the ranking feature to be specific."
 

Cons

"I notice that the schema visualizer can be improved. Additionally, the internal AI assistant powered by GPT can also be improved."
"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 think the support system can be better because after Supabase Vector stopped working in India, there is no support."
"It would be nice if all of this could be integrated all in one place with Supabase."
"One improvement I feel Supabase Vector could benefit from is that Supabase SDK stands out when comparing with a conventional Postgres SDK, and it would be even nicer if we could have a more direct way for access."
"Vespa has a considerable learning curve, making it challenging for most people to get into, and it is also expensive, which can deter startups or those with smaller budgets from using it."
"There were aspects of Vespa that needed improvement, such as if a monitoring dashboard were provided—and not only the monitoring dashboard, but also related supplementary tools for the administrative aspects—that would be better."
"We want Vespa to implement some UI features so that we can visualize how our data goes and what embeddings it stores."
"The integration is actually a pain."
 

Pricing and Cost Advice

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

By visitors reading reviews
Comms Service Provider
13%
Manufacturing Company
7%
Financial Services Firm
7%
Educational Organization
7%
Computer Software Company
16%
Comms Service Provider
12%
Financial Services Firm
9%
Healthcare Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise1
Large Enterprise3
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Supabase Vector?
I do not feel anything special about the pricing, setup cost, and licensing; we just regularly pay whatever we need, and I do not feel much difference.
What needs improvement with Supabase Vector?
One improvement I feel Supabase Vector could benefit from is that Supabase SDK stands out when comparing with a conventional Postgres SDK, and it would be even nicer if we could have a more direct ...
What is your primary use case for Supabase Vector?
Our main use case for Supabase Vector is to use pgvector as the vector database solution to store our embeddings for large language model applications. A specific example of how I'm using Supabase ...
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Comparisons

 

Overview

 

Sample Customers

Information Not Available
1. Yahoo 2. Verizon Media 3. Oath 4. Tumblr 5. AOL 6. Huffington Post 7. TechCrunch 8. Engadget 9. MapQuest 10. Moviefone 11. Autoblog 12. AOL Mail 13. Yahoo Mail 14. Yahoo Finance 15. Yahoo Sports 16. Yahoo News 17. Yahoo Search 18. Yahoo Answers 19. Yahoo Messenger 20. Yahoo Groups 21. Yahoo Weather 22. Yahoo Maps 23. Yahoo Fantasy Sports 24. Yahoo TV 25. Yahoo Movies 26. Yahoo Music 27. Yahoo Style 28. Yahoo Beauty 29. Yahoo Travel 30. Yahoo Autos 31. Yahoo Health 32. Yahoo Tech
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