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Marqo Agentic Search & Product Discovery vs Qdrant comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 13, 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

Marqo Agentic Search & Prod...
Ranking in Vector Databases
20th
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
Search as a Service (18th)
Qdrant
Ranking in Vector Databases
4th
Average Rating
9.0
Reviews Sentiment
4.8
Number of Reviews
2
Ranking in other categories
Open Source Databases (11th), AI Data Analysis (17th)
 

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of Marqo Agentic Search & Product Discovery is 1.0%, up from 0.4% compared to the previous year. The mindshare of Qdrant is 7.6%, up from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Qdrant7.6%
Marqo Agentic Search & Product Discovery1.0%
Other91.4%
Vector Databases
 

Featured Reviews

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Manideep - PeerSpot reviewer
AI Developer at Hecta.ai
Vector search has transformed support workflows and drives faster, more accurate responses
Qdrant can be improved in several ways. A dashboard or UI for re-indexing large collections without downtime and performance degradation would be valuable. The ecosystem around managed backups and cross-region replication could be more seamless for global deployments. Built-in analytics or observability tooling, such as a query performance dashboard and index health monitor, would reduce reliance on external tools. Tighter integration with popular orchestration frameworks like LangChain and LlamaIndex out of the box and more intuitive documentation would be very helpful. Developers need parameters for advanced fine-tuning, such as HNSW settings, and documentation could be clearer. For people without much experience in AI frameworks or vector databases, easier documentation would be helpful. At least the setup part could be simpler. These are some negatives I am observing.
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Top Industries

By visitors reading reviews
No data available
Computer Software Company
12%
Financial Services Firm
11%
Comms Service Provider
11%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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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?
I should check if real-time data updates in Qdrant have helped improve my models, as I don't even know they have that feature. A lot of our work is agentic right now, and we have also segmented the...
What is your primary use case for Qdrant?
My primary use cases for Qdrant are legal and educational.
 

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.Nike 20.Oracle 21.PG 22. PepsiCo 23.Procter and Gamble 24.Samsung 25. Shell  26.Sony 27. Toyota 28.Visa 29.Walmart 30.WeWork
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 Microsoft, Elastic, Redis and others in Vector Databases. Updated: March 2026.
884,797 professionals have used our research since 2012.