Pinecone vs Supabase Vector comparison

Pinecone and Supabase are both solutions in the Vector Databases category. Pinecone is ranked #6 with an average rating of 8.3, while Supabase is ranked #12 with an average rating of 9.0. Pinecone holds a 7.3% mindshare in VD, compared to Supabase’s 10.4% mindshare. Additionally, 100% of Pinecone users are willing to recommend the solution, compared to 100% of Supabase users who would recommend it.

Pinecone

Read 9 Pinecone reviews

3,250 Views
3,153 Comparison Views

100% willing to recommend

Supabase Vector

Read 3 Supabase Vector reviews

2,284 Views
2,284 Comparison Views

100% willing to recommend

Pinecone

Supabase Vector

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 5, 2025

Pinecone and Supabase Vector compete in the vector data management category. Pinecone seems to have the upper hand in scalability and integration, while Supabase Vector is more comprehensive in database management.

Features: Pinecone offers high-speed performance, real-time updates, and seamless integration with machine learning pipelines. Supabase Vector includes integrated authentication, API management, and collaboration tools.

Ease of Deployment and Customer Service: Pinecone provides a streamlined deployment with minimal configuration and responsive customer service. Supabase Vector is open-source with extensive documentation supporting community-driven assistance.

Pricing and ROI: Pinecone's pricing model is straightforward, suitable for scalable applications with a focus on performance. Supabase Vector offers a flexible pricing scheme, accommodating tailored solutions but with higher initial setup costs.

To learn more, read our detailed Pinecone vs. Supabase Vector Report (Updated: December 2025).

Buyer's Guide

Pinecone vs. Supabase Vector

December 2025

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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

Pinecone

Ranking in Vector Databases

6th

Average Rating

8.4

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

AI Data Analysis (14th), AI Content Creation (3rd)

Supabase Vector

Ranking in Vector Databases

12th

Average Rating

9.0

Reviews Sentiment

5.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Vector Databases category, the mindshare of Pinecone is 7.3%, down from 8.3% compared to the previous year. The mindshare of Supabase Vector is 10.4%, up from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Pinecone	7.3%
Supabase Vector	10.4%
Other	82.3%

Vector Databases

Featured Reviews

Pradeep Gudipati

Chief Technology Advisor at Kovaad technologies Pvt Ltd

Faced challenges with metadata filtering but have achieved reliable long-term memory for chat applications

We were looking at multiple options for a vector database, and we found Pinecone to be the easiest to integrate into our solution. Plus, it has a very generous free tier, which helps us as a startup. The best features Pinecone offers are quick setup and good indexing for us. The retrieval mechanisms are fast, and the integration with Python as with JavaScript and TypeScript libraries that Pinecone provides are very robust. Authentication is also very good. The namespaces feature allows us to break down or store data for each user separately, reducing interference and maintaining privacy as an important feature. Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database. We are seeing that the trainees getting trained on the platform are more satisfied with the results or messages generated by AI.

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Kaustubh Sule

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.

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

"The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes."

"The semantic search capability is very good."

"Pinecone has positively impacted my organization by helping people in needle-in-a-haystack situations, as previously they had to grind through PDF documents, PowerPoint documents, and websites, but now with Pinecone, they can ask questions and receive references to documents along with the page numbers where that information exists, so they can use it as a reference or backtrack, especially for things such as FDA approvals where they can quote the exact page number from PDF documents, eliminating hallucination and providing real-time data that relies on an external vector database with enough guardrails to ensure it won't provide information not in the vector database, confining it to the information present in the indexes."

"The best thing about Pinecone is its private local host feature. It displays all the maintenance parameters and lets us view the data sent to the database. We can also see the status of the CD and which application it corresponds to."

"The product's setup phase was easy."

"We chose Pinecone because it covers most of the use cases."

"Pinecone has positively impacted our organization by enhancing efficiency for the team, and the long-term effect has been that the chats have become much more personalized due to the memory added through a vector database."

"The most valuable feature of Pinecone is its managed service aspect. There are many vector databases available, but Pinecone stands out in the market. It is very flexible, allowing us to input any kind of data dimensions into the platform. This makes it easy to use for both technical and non-technical users."

More Pinecone pros

"The platform's role-level security feature is quite effective for spatial data management."

"The tool is easy to use."

"Supabase enables us to lower the skill floor while keeping the ceiling high."

Cons

"Pinecone is good as it is, but had it been on AWS infrastructure, we wouldn't experience some network lags because it's outside AWS."

"For testing purposes, the product should offer support locally as it is one area where the tool has shortcomings."

"The tool does not confirm whether a file is deleted or not."

"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."

"Onboarding could be better and smoother."

"If Pinecone gave us RAG as a service, we'd be more than happy to use that."

"One major issue I have noticed with Pinecone is that it does not allow me to search based on metadata."

"Pinecone can be made more budget-friendly."

More Pinecone cons

"The support for React Native CLI is an area with certain shortcomings where improvements are required."

"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."

Pricing and Cost Advice

"Pinecone is not cheap; it's actually quite expensive. We find that using Pinecone can raise our budget significantly. On the other hand, using open-source options is more budget-friendly."

"I have experience with the tool's free version."

"The solution is relatively cheaper than other vector DBs in the market."

"I think Pinecone is cheaper to use than other options I've explored. However, I also remember that they offer a paid version."

"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."

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Top Industries

By visitors reading reviews

Computer Software Company

14%

Manufacturing Company

Comms Service Provider

Financial Services Firm

Comms Service Provider

15%

Computer Software Company

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	3

No data available

Questions from the Community

What do you like most about Pinecone?

We chose Pinecone because it covers most of the use cases.

See all answers

What needs improvement with Pinecone?

I give Pinecone a nine out of ten because I hope it provides an end-to-end agentic solution, but currently, it doesn't have those agentic capabilities, meaning I have to create a Streamlit applicat...

See all answers

What is your primary use case for Pinecone?

My main use case for Pinecone is creating vector indexes for GenAI applications. A specific example of how I use Pinecone in one of my projects is utilizing a RAG pipeline where I take text from PD...

See all answers

What is your experience regarding pricing and costs for Supabase Vector?

The price is good.

See all answers

What needs improvement with Supabase Vector?

I think there are still many Postgres features that can be developed further by the Supabase team.

See all answers

What is your primary use case for Supabase Vector?

I am exploring Supabase for my project on UMKM.

See all answers

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Compared 25% of the time

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Compared 8% of the time

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Compared 6% of the time

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Product Reports

Buyer's Guide

Pinecone

January 2026

Download Pinecone product report

Buyer's Guide

Vector Databases

December 2025

Download Supabase Vector product report

Overview

Pinecone is a powerful tool for efficiently storing and retrieving vector embeddings. It is highly praised for its scalability, speed, and ease of integration with existing workflows.

Users find it particularly useful for similarity search, recommendation systems, and natural language processing.

Its efficient search capabilities, seamless integration with existing systems, and ability to handle large-scale datasets make it a valuable tool for data analysis and retrieval.

Pinecone

Supabase Vector offers an efficient way to manage and query vector embeddings, catering to the needs of developers and data scientists seeking scalable solutions for vector-based data handling.

Supabase Vector is designed to streamline the process of storing, managing, and querying vector embeddings, essential for applications like machine learning algorithms and personalized recommendations. Its intuitive API and integration capabilities make it a preferred choice for tech professionals seeking a reliable backend for their vector data requirements. With flexible storage options and robust querying features, it accommodates the dynamic demands of AI-driven projects.

What are its key features?

Seamless Integration: Connects effortlessly with databases, making it simple to incorporate into existing projects.
Scalable Storage: Allows for efficient storage of large volumes of vector data, accommodating growth in usage.
Flexible Queries: Supports complex queries, facilitating advanced data analysis and insights.
Real-Time Updates: Ensures that data remains current with instantaneous updates.
Developer-Friendly: Comes with comprehensive documentation and an intuitive API for ease of use.

What benefits or ROI should users look for?

Increased Efficiency: Streamlines data management, reducing time spent on backend development.
Cost Effectiveness: Offers scalable options that can save on infrastructure and maintenance costs.
Enhanced Accuracy: Delivers precise query results, improving decision-making processes.
Improved Developer Productivity: Simplifies complex tasks, allowing developers to focus on more critical activities.

Supabase Vector can be particularly beneficial in industries such as e-commerce for personalized product recommendations, in finance for fraud detection through pattern analysis, and in healthcare for patient data insights. Its capability to handle diverse sets of embeddings makes it versatile across different sectors needing robust data processing tools.

Supabase

Sample Customers

1. Airbnb 2. DoorDash 3. Instacart 4. Lyft 5. Pinterest 6. Reddit 7. Slack 8. Snapchat 9. Spotify 10. TikTok 11. Twitter 12. Uber 13. Zoom 14. Adobe 15. Amazon 16. Apple 17. Facebook 18. Google 19. IBM 20. Microsoft 21. Netflix 22. Salesforce 23. Shopify 24. Square 25. Tesla 26. TikTok 27. Twitch 28. Uber Eats 29. WhatsApp 30. Yelp 31. Zillow 32. Zynga

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Buyer's Guide

Pinecone vs. Supabase Vector

December 2025

Free Report: Pinecone vs. Supabase Vector

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