PostgreSQL vs Supabase comparison

PostgreSQL and Supabase are both solutions in the Vector Databases category. PostgreSQL is ranked #7 with an average rating of 8.7, while Supabase is ranked #2 with an average rating of 8.6. PostgreSQL holds a 9.1% mindshare in VD, compared to Supabase’s 5.7% mindshare. Additionally, 96% of PostgreSQL users are willing to recommend the solution, compared to 100% of Supabase users who would recommend it.

PostgreSQL

Read 128 PostgreSQL reviews

12,746 Views
5,226 Comparison Views

96% willing to recommend

Supabase

Read 14 Supabase reviews

3,318 Views
3,318 Comparison Views

100% willing to recommend

PostgreSQL

Supabase

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Jul 22, 2026

PostgreSQL and Supabase Vector are both powerful database solutions competing in the database management space. Based on the data comparisons in each section, PostgreSQL has the upper hand in terms of scalability and robustness, while Supabase Vector excels in ease of setup and AI-driven application integration.

Features: PostgreSQL offers robust spatial support for GIS applications, powerful extensions like PostGIS, and reliable high availability through features such as Multi-Master Replication. It excels in performance, reliability, and scalability, making it a preferred choice for complex query handling in production environments. Supabase Vector provides hybrid SQL and vector search capabilities, emphasizing ease of setup and integration for modern applications with a focus on backend functionality and security, enhancing both structured and unstructured data handling.

Room for Improvement: PostgreSQL could enhance user-friendly features like input/output tools and introduce easier ways to manage multi-master replication and complex analytic functions, needing documentation improvements. Supabase Vector could improve the onboarding experience for new users and provide enhanced documentation for complex use cases while working on built-in hybrid search support and large-scale performance tuning.

Ease of Deployment and Customer Service: PostgreSQL is widely deployed across hybrid and on-premises environments, offering community support and a strong ecosystem of forums and resources, despite lacking formal central support. Supabase, with a focus on public and hybrid cloud environments, provides integrated support but faces regional support challenges, with users often relying on community resources and online documentation.

Pricing and ROI: PostgreSQL is fully open-source, offering zero licensing fees, leading to high ROI by minimizing initial investment. Supabase Vector charges based on usage tiers, with a free tier providing substantial capabilities, supporting medium-sized applications without significant cost inflation and delivering significant ROI for businesses integrating AI functionalities.

To learn more, read our detailed PostgreSQL vs. Supabase Report (Updated: June 2026).

Buyer's Guide

PostgreSQL vs. Supabase

June 2026

Download the complete report

Helped 906,418 peers since 2012

Review summaries and opinions

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

ROI

Sentiment score

6.7

PostgreSQL offers cost savings and rapid ROI with free open-source capabilities, ideal for startups and growing enterprises.

Sentiment score

5.3

Supabase Vector boosts efficiency and profitability with faster development, better user engagement, reduced costs, and higher conversion rates.

No quotes available

For more quotes and insights, download the PostgreSQL report

The dashboard's management made access straightforward for users and super easy to maintain, resulting in very few errors.

Samir Patil

Co-Founder & CTO at Mango Giraffe

We notice significant improvements when measuring metrics such as average response times, which have shifted from 800 milliseconds to 2.5 seconds down to around 200 milliseconds to 800 milliseconds, with click-through rates for recommendations improving by 45 to 70%.

reviewer2848647

Product Engineer at a tech vendor with 11-50 employees

The use of these technologies definitely impacts reducing the time and cost of implementation or deployment.

Alberto Hidalgo

Co-Founder at a tech services company with 1-10 employees

For more quotes and insights, download the Supabase report

Customer Service

Sentiment score

6.7

PostgreSQL support is strong with community forums, detailed documentation, and high-rated resources, offering both free and paid options.

Sentiment score

5.4

Supabase users find customer service satisfactory with efficient support and resources, enhancing their platform experience with minimal direct assistance.

If PostgreSQL is hosted on cloud services such as Amazon RDS or Google Cloud SQL, the support is handled by the cloud provider, who provides automated backups, monitoring, infrastructure management, and technical support tickets.

AyushVerma

Software Engineer at GSS Academy, Noida

Overall, we have a very small customer service team and a good engineering team with no overburden or bandwidth issues.

Shobhit Goel

Data Science Architect at publicis Sapient

For customizations and extensions, the community is very active and useful.

Ram Maruboina

Software Engineer – Rust Systems & AI Evaluation at Turing

For more quotes and insights, download the PostgreSQL report

I would rate the customer support a nine since they replied quickly and answered my questions properly, which helped me a lot.

Samir Patil

Co-Founder & CTO at Mango Giraffe

I have always been able to solve it out with the help of my community or sometimes YouTube.

FavourEmosivbe

Automation Specialist at a consultancy with 11-50 employees

Community support from helpful developers and engineers provides fast responses on GitHub issues and community forums.

Boya Uday Kumar

AI Solutions Lead at ADP

For more quotes and insights, download the Supabase report

Scalability Issues

Sentiment score

7.4

PostgreSQL is highly scalable, handling large on-premise or cloud deployments effectively, supporting high transactions and growing user demands.

Sentiment score

5.6

Supabase excels in small to medium applications but requires optimization for larger scales; free tier benefits startups.

Now, we are doing the same level of transactions in PostgreSQL, around 100,000 transactions, and we are getting good throughput with no latency.

Shobhit Goel

Data Science Architect at publicis Sapient

For more quotes and insights, download the PostgreSQL report

As we move toward larger scales, such as multi-million vectors, it requires careful engineering to maintain predictable performance.

reviewer2848647

Product Engineer at a tech vendor with 11-50 employees

I have basically used it for small teams, not large teams that need to cover thousands of users.

FavourEmosivbe

Automation Specialist at a consultancy with 11-50 employees

Supabase Vector is highly scalable for small to medium to large scale applications.

Boya Uday Kumar

AI Solutions Lead at ADP

For more quotes and insights, download the Supabase report

Stability Issues

Sentiment score

8.0

PostgreSQL is praised for its stability and reliability, outperforming MySQL, with issues mainly from misconfiguration, not intrinsic faults.

Sentiment score

7.6

Supabase Vector is stable and reliable, with occasional downtime in India, mainly due to coding errors, not the platform.

I have never seen any performance issue in PostgreSQL.

Shobhit Goel

Data Science Architect at publicis Sapient

For more quotes and insights, download the PostgreSQL report

From my experience, Supabase Vector is stable.

Alberto Hidalgo

Co-Founder at a tech services company with 1-10 employees

Achieving the best performance at higher scales depends largely on optimization of queries and indexes.

reviewer2848647

Product Engineer at a tech vendor with 11-50 employees

I basically use it for my web-coded apps and for the RAG agent and it does all of the needs that I want it to do for my project and for my client's project.

FavourEmosivbe

Automation Specialist at a consultancy with 11-50 employees

For more quotes and insights, download the Supabase report

Room For Improvement

PostgreSQL users seek improvements in interface, performance, scalability, integration, documentation, and support for large-scale real-time applications.

Supabase Vector needs improved documentation and support, better performance, scalability, indexing, and enhanced tool integration and language support.

PostgreSQL remains a strong choice for enterprise applications due to its stability, extensibility, and SQL standards compliance.

Ram Maruboina

Software Engineer – Rust Systems & AI Evaluation at Turing

Query optimization improves slow queries by using proper indexes, avoiding unnecessary joins, and using EXPLAIN ANALYZE to inspect query plans.

AyushVerma

Software Engineer at GSS Academy, Noida

If I need to increase the dimension to 3,000 or 5,000, that option should be available.

Shobhit Goel

Data Science Architect at publicis Sapient

For more quotes and insights, download the PostgreSQL report

Better query debugging tools and built-in evaluation toolkits for vector search would be incredibly helpful for developers.

reviewer2848647

Product Engineer at a tech vendor with 11-50 employees

If they could make the debugging process clearer to prevent the error messages, that will make development faster for web-coded apps.

FavourEmosivbe

Automation Specialist at a consultancy with 11-50 employees

For index optimization guidance, clearer instructions on when to use IVFFlat versus HNSW indexes would be helpful.

Boya Uday Kumar

AI Solutions Lead at ADP

For more quotes and insights, download the Supabase report

Setup Cost

PostgreSQL offers cost-effective scalability and flexibility with zero licensing fees, though setup and support may incur additional costs.

Supabase provides flexible pricing with a free tier and paid plans, ensuring scalability and cost efficiency for various projects.

Even with doing 100,000 transactions right now within PostgreSQL, we are happy with PostgreSQL and not seeing that it is expensive or going out of budget.

Shobhit Goel

Data Science Architect at publicis Sapient

The managed PostgreSQL itself is open source with no license fees.

Ram Maruboina

Software Engineer – Rust Systems & AI Evaluation at Turing

For more quotes and insights, download the PostgreSQL report

It was amazing to be able to create all this technology for free, without the need to pay additional costs to use those technologies, apart from the embeddings ones from Google.

Alberto Hidalgo

Co-Founder at a tech services company with 1-10 employees

For now, I think the pricing is perfect because every business person can afford it and a developer can afford that price.

FavourEmosivbe

Automation Specialist at a consultancy with 11-50 employees

I utilize the free tier, which includes a 500 MB database with vector support at no cost, allowing support for millions of embeddings.

Boya Uday Kumar

AI Solutions Lead at ADP

For more quotes and insights, download the Supabase report

Valuable Features

PostgreSQL excels in spatial support, high availability, JSONB handling, integration, scalability, and community-driven advanced features for diverse applications.

Supabase Vector offers easy setup, cost-efficiency, PostgreSQL, SQL with vector search, improving database operations through streamlined, secure features.

PostgreSQL improves reliability, performance, and scalability in production. Since it is ACID compliant, it ensures that database transactions are safe and consistent, preventing partial data updates, maintaining data integrity, and allowing multiple users to read or write data simultaneously using MVCC.

AyushVerma

Software Engineer at GSS Academy, Noida

The best feature is performance, because of which I decided on PostgreSQL.

Shobhit Goel

Data Science Architect at publicis Sapient

Its robustness and reliability are incredible and stable, which is crucial for critical data, especially with AI model outputs.

Ram Maruboina

Software Engineer – Rust Systems & AI Evaluation at Turing

For more quotes and insights, download the PostgreSQL report

We have Supabase basically as the host of most of our business relational database and user data, so since the client's applications are migrating to language model-empowered features, it is very useful, and we do not need to register for other database types.

Daniel Pan

Director at a tech services company with 1-10 employees

Supabase Vector is a managed service, so I do not need to worry about scaling the database and managing the infrastructure.

reviewer2849445

Senior Full Stack Engineer at a tech vendor with 11-50 employees

Supabase Vector has positively impacted my organization by significantly reducing our testing time.

Samir Patil

Co-Founder & CTO at Mango Giraffe

For more quotes and insights, download the Supabase report

Categories and Ranking

PostgreSQL

Ranking in Vector Databases

7th

Average Rating

8.4

Reviews Sentiment

7.4

Number of Reviews

128

Ranking in other categories

Open Source Databases (2nd)

Supabase

Ranking in Vector Databases

2nd

Average Rating

8.6

Reviews Sentiment

5.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2026, in the Vector Databases category, the mindshare of PostgreSQL is 9.1%, up from 5.1% compared to the previous year. The mindshare of Supabase is 5.7%, down from 8.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
Supabase Vector	5.7%
PostgreSQL	9.1%
Other	85.2%

Vector Databases

Featured Reviews

Shobhit Goel

Data Science Architect at publicis Sapient

High-volume transactions have reduced failures and improve customer service efficiency

The best feature is performance, because of which I decided on PostgreSQL. I have also enabled the PG vector plugin on top of PostgreSQL. I have the opportunity to use two different features and two different flavors in a single product, which is the best thing about PostgreSQL. Initially, we had some hiccups around the performance part, but later we did indexing in PostgreSQL and now it is working very well. Even when we are doing 100,000 transactions in a day, PostgreSQL is working excellently. The interface is another best feature. If I need to do any query, I simply install the plugin on my local, which is pgAdmin. Through pgAdmin, I am able to communicate with PostgreSQL and execute all my SQL queries. I am getting a better UI with PostgreSQL as the backend, which is also one of the best options. PG vector is also very strong from PostgreSQL where I have implemented RAG and on a daily basis, I inject thousands of pages of PDF. More than 100 PDFs are coming into my system and one PDF is around 1,000 pages. We are injecting them into PostgreSQL and converting them into dimensions and inserting them into PG vector. The level of transactions we are doing on a daily basis is substantial, and we are getting very good throughput and low latency from PostgreSQL. When we were doing more than 50,000 transactions in a minute with the previous database, we were getting a lot of latency issues with threads getting blocked and abruptly closed unwantedly. After doing extensive research, we decided to move to PostgreSQL. Now, we are doing around 100,000 transactions in PostgreSQL and we are getting good throughput with no latency.

Read full review

Boya Uday Kumar

AI Solutions Lead at ADP

Semantic search has transformed client sites and drives faster projects with higher conversions

Adapting to Supabase Vector was relatively smooth, but there was definitely a moderate learning curve at the start. The SQL foundation, REST API, documentation, and integration with all the AI tools made it easier. However, understanding embeddings, index types, similarity metrics, and how SQL and vector hybrid queries work, as well as the RLS policies for vectors, required some time to learn. I do not have many things to point out, but a couple of areas for improvement come to mind. For index optimization guidance, clearer instructions on when to use IVFFlat versus HNSW indexes would be helpful. Additionally, having a built-in embedding generation capability would simplify the workflow, as currently, I use external services such as OpenAI or Hugging Face for that purpose.

Read full review

See which vendors are best for you

Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.

See recommendations

906,418 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

11%

Comms Service Provider

10%

Computer Software Company

10%

Outsourcing Company

Comms Service Provider

13%

Manufacturing Company

10%

Educational Organization

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	58
Midsize Enterprise	26
Large Enterprise	49

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	1
Large Enterprise	7

Questions from the Community

How does Firebird SQL compare with PostgreSQL?

PostgreSQL was designed in a way that provides you with not only a high degree of flexibility but also offers you a cheap and easy-to-use solution. It gives you the ability to redesign and audit yo...

See all answers

What is your experience regarding pricing and costs for PostgreSQL?

I purchased from the marketplace, so licensing and pricing cost is acceptable. To be honest, there is a separate team who handles the cost of licensing everything. I have admin access on Azure and ...

See all answers

What needs improvement with PostgreSQL?

The only thing for PG vector is if the dimension limit could be increased. Currently, the dimension limit is around 1,000 to 1,052. If I need to increase the dimension to 3,000 or 5,000, that optio...

See all answers

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

In this basic implementation or proof of concept project, I use the basic Supabase project available in the free trial. I am not sure which one of those options it falls under, but I use the free S...

See all answers

What needs improvement with Supabase Vector?

When setting up a database, a PostgreSQL instance, which is the most popular use of Supabase, instead of having to go and write and run an SQL line to create a pgvector on Supabase, it would be nic...

See all answers

What is your primary use case for Supabase Vector?

As an AI Engineer, my primary use case of Supabase Vector is for storing vector databases that I use at retrieval and inference in my AI agent and RAG pipelines. I have been working with RAG soluti...

See all answers

Comparisons

Firebird SQL vs PostgreSQL

Compared 12% of the time

MySQL vs PostgreSQL

Compared 7% of the time

MariaDB vs PostgreSQL

Compared 7% of the time

LanceDB vs PostgreSQL

Compared 5% of the time

Chroma vs PostgreSQL

Compared 5% of the time

Product Reports

Buyer's Guide

PostgreSQL

July 2026

Download PostgreSQL product report

Buyer's Guide

Supabase

June 2026

Download Supabase product report

Overview

PostgreSQL is a versatile and reliable database management system commonly used for web development, data analysis, and building scalable databases.

It offers advanced features like indexing, replication, and transaction management. Users appreciate its flexibility, performance, and ability to handle large amounts of data efficiently. Its robustness, scalability, and support for complex queries make it highly valuable.

Additionally, PostgreSQL's extensibility, flexibility, community support, and frequent updates contribute to its ongoing improvement and stability.

PostgreSQL

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. Apple 2. Cisco 3. Fujitsu 4. Instagram 5. Netflix 6. Red Hat 7. Sony 8. Uber 9. Cisco Systems 10. Skype 11. LinkedIn 12. Etsy 13. Yelp 14. Reddit 15. Dropbox 16. Slack 17. Twitch 18. WhatsApp 19. Snapchat 20. Shazam 21. SoundCloud 22. The New York Times 23. Cisco WebEx 24. Atlassian 25. Cisco Meraki 26. Heroku 27. GitLab 28. Zalando 29. OpenTable 30. Trello 31. Square Enix 32. Bloomberg

Information Not Available

Buyer's Guide

PostgreSQL vs. Supabase

June 2026

Free Report: PostgreSQL vs. Supabase

Find out what your peers are saying about PostgreSQL vs. Supabase and other solutions. Updated: June 2026.

DOWNLOAD NOW

906,418 professionals have used our research since 2012.

See our PostgreSQL vs. Supabase report.

See our list of best Vector Databases vendors.

We monitor all Vector Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.