Try our new research platform with insights from 80,000+ expert users

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
11th
Average Rating
10.0
Reviews Sentiment
4.8
Number of Reviews
1
Ranking in other categories
Open Source Databases (16th), AI Data Analysis (27th)
 

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of Marqo Agentic Search & Product Discovery is 0.9%, up from 0.4% compared to the previous year. The mindshare of Qdrant is 8.0%, up from 7.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
Qdrant8.0%
Marqo0.9%
Other91.1%
Vector Databases
 

Featured Reviews

Use Marqo Agentic Search & Product Discovery?
Leave a review
AT
Chief Ai Scientist at Predictive Systems
Hybrid search has improved legal and educational AI retrieval and supports fast model iteration
Currently, we are using a vector database called Qdrant, but most of our tasks are agentic, and we don't have it anymore. I can answer a few questions about Qdrant. I have used Qdrant's hybrid search capability. The use of multiple query languages has impacted my data query processes mostly as Q&A. We use the Ragas metrics to evaluate Qdrant's performance in indexing and retrieving vectors. All the metrics I consider in Ragas are useful. In my company, we have around eight or nine people using Qdrant. I think Qdrant is popular enough in my region, but they can probably promote it more. I rate this review a 9 out of 10.
report
Use our free recommendation engine to learn which Vector Databases solutions are best for your needs.
882,961 professionals have used our research since 2012.
 

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
 

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: January 2026.
882,961 professionals have used our research since 2012.