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PostgreSQL vs Qdrant 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:
 

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
5.1
Qdrant reduces costs and enhances productivity with efficient integration, open-source benefits, and improved pipeline processing, despite database issues.
Thanks to Qdrant's open-source nature, our initial licensing and setup costs were nearly zero, allowing for swift testing and launch of our RAG prototype.
Automation Engineer at a educational organization with 11-50 employees
The time saved is substantial, with nearly three weeks or more for projects deployed with Qdrant Cloud in no-code platforms.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
I have seen a significant return on investment from using Qdrant because it is very easy to integrate and highly efficient, saving a lot of time in my day-to-day operations, which ultimately saves money as well.
Product Engineer at a tech vendor with 11-50 employees
 

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
4.3
Qdrant's open-source nature fosters effective community-driven support, with well-rated online resources addressing most user queries efficiently.
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.
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.
Data Science Architect at publicis Sapient
For customizations and extensions, the community is very active and useful.
Software Engineer – Rust Systems & AI Evaluation at Turing
It's open source, so we house it on our server.
Chief Ai Scientist at Predictive Systems
The documentation provided by Qdrant covers most queries effectively.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
I rate the technical support of Qdrant as a nine because I think we have never reached out to them directly, but Qdrant has good support available online, and I can get answers from forums.
Co Founder & CEO at SaYukth Private Limited
 

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
5.3
Qdrant offers efficient scalability and performance, effectively managing increased workloads and easily integrating with custom database services.
Now, we are doing the same level of transactions in PostgreSQL, around 100,000 transactions, and we are getting good throughput with no latency.
Data Science Architect at publicis Sapient
In the recruiting agency project, the reliance on the vector database has expanded from storing hundreds of resumes to thousands.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
When Qdrant is deployed in Docker, it scales really fast, and you can assign multiple CPUs to enhance performance.
Analyst at Synergy Connect
Qdrant handles growing workloads and data volumes well for me, which was a significant reason for my shift from other popular alternatives to Qdrant.
Product Engineer at a tech vendor with 11-50 employees
 

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
7.8
Qdrant is praised for stability and ease of use, with minor update needs and efficient file lock system.
I have never seen any performance issue in PostgreSQL.
Data Science Architect at publicis Sapient
You need to patch Qdrant as soon as patches are released.
Co Founder & CEO at SaYukth Private Limited
It is easy to use whether on LangChain or on its own.
Product Engineer at a tech vendor with 11-50 employees
Qdrant is stable, except for the limitation concerning the termination of inactive clouds after a week.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
 

Room For Improvement

PostgreSQL users seek improvements in interface, performance, scalability, integration, documentation, and support for large-scale real-time applications.
Qdrant could improve with UI updates, better integration, simplified setup, enhanced clustering, and support for analytics and image vectorization.
PostgreSQL remains a strong choice for enterprise applications due to its stability, extensibility, and SQL standards compliance.
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.
Software Engineer at GSS Academy, Noida
If I need to increase the dimension to 3,000 or 5,000, that option should be available.
Data Science Architect at publicis Sapient
Fast large-scale filtering operations could be implemented, such as automatic index suggestions, adaptive query planning, and smart indexing of metadata fields, which would make Qdrant even more efficient.
Product Engineer at a tech vendor with 11-50 employees
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.
Co Founder & CEO at SaYukth Private Limited
Incorporating embedding features directly in Qdrant Cloud would eliminate the need to depend on external solutions.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
 

Setup Cost

PostgreSQL offers cost-effective scalability and flexibility with zero licensing fees, though setup and support may incur additional costs.
Qdrant's open-source model minimizes setup costs, though developer time and paid plans can increase expenses; Supabase offers savings.
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.
Data Science Architect at publicis Sapient
The managed PostgreSQL itself is open source with no license fees.
Software Engineer – Rust Systems & AI Evaluation at Turing
Using Qdrant is free.
Chief Ai Scientist at Predictive Systems
Regarding pricing, setup costs, and licensing, since I am using only the free tier of Qdrant Cloud, there are no setup costs involved.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
Licensing posed no issues, as Qdrant is open-source software with no upfront fees.
Automation Engineer at a educational organization with 11-50 employees
 

Valuable Features

PostgreSQL excels in spatial support, high availability, JSONB handling, integration, scalability, and community-driven advanced features for diverse applications.
Qdrant excels with hybrid search, cost-efficient cloud, Python support, high-speed queries, and no-code deployment for user satisfaction.
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.
Software Engineer at GSS Academy, Noida
The best feature is performance, because of which I decided on PostgreSQL.
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.
Software Engineer – Rust Systems & AI Evaluation at Turing
The ability of Qdrant to handle high-dimensional vectors for my AI projects is pretty fast, and I think it's the best we have used so far.
Chief Ai Scientist at Predictive Systems
An accuracy boost was definitely observed from 45 to 50% using Faiss to around 85 to 95% using Qdrant, and the users are really happy as they are getting suggested really good schemes that would take a lot of time to find.
Analyst at Synergy Connect
Qdrant supports high-dimension vectors and cosine similarity, which any vector database should have, and it is pretty fast.
CTO at HoneyComb AI
 

Categories and Ranking

PostgreSQL
Ranking in Open Source Databases
2nd
Ranking in Vector Databases
7th
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
128
Ranking in other categories
No ranking in other categories
Qdrant
Ranking in Open Source Databases
8th
Ranking in Vector Databases
4th
Average Rating
8.8
Reviews Sentiment
5.4
Number of Reviews
8
Ranking in other categories
AI Data Analysis (10th)
 

Mindshare comparison

As of August 2026, in the Open Source Databases category, the mindshare of PostgreSQL is 12.6%, down from 17.2% compared to the previous year. The mindshare of Qdrant is 4.4%, up from 3.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Open Source Databases Mindshare Distribution
ProductMindshare (%)
PostgreSQL12.6%
Qdrant4.4%
Other83.0%
Open Source Databases
 

Featured Reviews

Shobhit Goel - PeerSpot reviewer
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.
Chirag Morajkar - PeerSpot reviewer
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 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.
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Comms Service Provider
9%
Computer Software Company
9%
Construction Company
8%
Comms Service Provider
11%
Manufacturing Company
11%
Financial Services Firm
10%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business58
Midsize Enterprise26
Large Enterprise49
By reviewers
Company SizeCount
Small Business10
 

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...
What is your experience regarding pricing and costs for PostgreSQL?
I am not directly involved in the licensing or procurement decisions, so I cannot comment in detail on the price. From an engineering perspective, PostgreSQL is cost-efficient because it is open so...
What needs improvement with PostgreSQL?
While improving reliability, I have noticed that the limitations in PostgreSQL can be complex. For large-scale deployments, configuration, performance tuning, and related tasks can be complex and i...
What is your experience regarding pricing and costs for Qdrant?
Licensing posed no issues, as Qdrant is open-source software with no upfront fees. Initially, the setup cost was low since we utilized a self-hosted model on a small cloud VM. However, as we added ...
What needs improvement with Qdrant?
The UI can be a bit better, but that is just my own personal opinion. Qdrant is pretty good overall, but it can be improved. For example, the UI could be better, and it has pretty much very generic...
What is your primary use case for Qdrant?
I have been designing vector databases, so I use Qdrant mostly to explore how the engineers at Qdrant have built the whole vector database, specifically the multi-vector system. In terms of usage, ...
 

Comparisons

 

Overview

 

Sample Customers

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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
Find out what your peers are saying about PostgreSQL vs. Qdrant and other solutions. Updated: July 2026.
908,800 professionals have used our research since 2012.