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Chroma vs Qdrant comparison

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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:
 

Categories and Ranking

Chroma
Ranking in Vector Databases
17th
Average Rating
8.6
Reviews Sentiment
5.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Qdrant
Ranking in Vector Databases
2nd
Average Rating
8.8
Reviews Sentiment
5.8
Number of Reviews
10
Ranking in other categories
Open Source Databases (5th), AI Data Analysis (6th)
 

Mindshare comparison

As of September 2026, in the Vector Databases category, the mindshare of Chroma is 5.9%, down from 11.3% compared to the previous year. The mindshare of Qdrant is 6.3%, down from 8.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
Qdrant6.3%
Chroma5.9%
Other87.8%
Vector Databases
 

Featured Reviews

GagandeepSingh1 - PeerSpot reviewer
Data Science Manager at Zykrr
A simple and easy to use solution that can run on a two-course CPU
We collect customer's feedback, and then we present it to the clients It's very easy to set up and runs easily. It doesn't require great hardware and can run on a two-course CPU with four gigs. The hybrid algorithm needs improvement. I have been using Chroma for one year.  I had some trouble…
Pawel Cislo - PeerSpot reviewer
MLOps Engineer at a tech services company with 501-1,000 employees
Adaptive assistant has delivered faster grounded answers and has reduced token costs significantly
The main limitations I notice come down to developer experience and native features rather than performance. Building hybrid retrieval and fusion pipelines still requires considerable manual orchestration and code. Having more built-in multi-query fusion strategies natively inside Qdrant would be a significant time-saver. Additionally, managing dynamic metadata schemas and tracking index build progress during bulk ingest could be more transparent in the web UI. To make things easier for developers, Qdrant could provide more native tools for managing payload schema evolution over time. As metadata needs change in production RAG systems, updating existing payloads across large collections currently requires custom migration scripts. Built-in schema versioning and simpler automated index testing during CI/CD would make running Qdrant in rapidly evolving production environments even smoother. I rate Qdrant 9 out of 10 because its speed, sub-15 millisecond retrieval, and single-stage payload filtering make it top-tier for production RAG pipelines. I deduct one point mainly for developer experience. Setting up multi-query fusion still requires extra boilerplate code, payload metadata schema updates require custom migration scripts, and real-time visibility into HNSW graph indexing progress during bulk ingest could be improved in the web UI.

Quotes from Members

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

Pros

"It's very easy to set up and runs easily."
"The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it."
"Qdrant has positively impacted my organization by consuming much less time than building systems through coding."
"Qdrant has positively impacted my organization mainly by reducing usage costs for AI because in the older system, in order to get the context, we were just dumping everything into the system, which would inflate the cost of the API, whatever AI we were using, such as OpenAI or Claude."
"Qdrant has positively impacted my organization by significantly improving our RAG system's latency, cost-efficiency, and accuracy."
"Qdrant is one of the best vector databases out there that is also open source."
"Using Qdrant's hybrid search capability has improved my search results."
"Qdrant is a good and scalable vector database, and it is free."
"Qdrant is an excellent vector database that anyone would want to use with RAG AI."
"Qdrant has reduced our response time to less than one second for our 128 KB token sizes, and we are satisfied with that performance."
 

Cons

"The hybrid algorithm needs improvement."
"I think Chroma doesn't have a ready-made containerized image available."
"Qdrant is pretty good overall, but it can be improved. For example, the UI could be better, and it has pretty much very generic features that every other vector database provides."
"There can always be improvements needed for Qdrant, but I do not want to add anything at this time."
"Qdrant is available through a containerized Docker, but a normal deployment in Qdrant is not there, and that can actually be worked out."
"Architectural complexity was a key friction point, as our primary database was set in Supabase, necessitating synchronization of two separate systems for user data, permissions, and states."
"The area for improvement in Qdrant is its clustering capability. 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."
"One of the key limitations is that Qdrant does not have built-in role-based access control, and while being self-hosted is a benefit, it can also be improved."
"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."
"A lot of our work is agentic right now, and we have also segmented the content to be logical, so there's not a lot of vector search anymore."
 

Pricing and Cost Advice

"The current version is an open-source."
Information not available
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Top Industries

By visitors reading reviews
Computer Software Company
11%
Financial Services Firm
11%
Comms Service Provider
9%
Manufacturing Company
8%
Comms Service Provider
13%
Manufacturing Company
11%
Financial Services Firm
10%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise2
 

Questions from the Community

Ask a question
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What is your experience regarding pricing and costs for Qdrant?
I find Qdrant's pricing and licensing extremely straightforward and cost-effective. The core product is open source under Apache 2.0, so initial experimentation and local integration testing cost n...
What needs improvement with Qdrant?
Qdrant is available through a containerized Docker, but a normal deployment in Qdrant is not there, and that can actually be worked out. That was one aspect I thought about, because I need to have ...
What is your primary use case for Qdrant?
We have a full-fledged RAG system using Qdrant Vector Database, and that is how it has benefited us. For example, we have implemented a techno-commercial evaluator using that, and it is in producti...
 

Comparisons

 

Overview

 

Sample Customers

1. Google 2. Netflix 3. Amazon 4. Facebook 5. Microsoft 6. Apple 7. Twitter 8. Spotify 9. Adobe 10. Uber 11. Airbnb 12. LinkedIn 13. Pinterest 14. Snapchat 15. Dropbox 16. Salesforce 17. IBM 18. Intel 19. Oracle 20. Cisco 21. HP 22. Dell 23. Samsung 24. Sony 25. LG 26. Panasonic 27. Philips 28. Toshiba 29. Nokia 30. Motorola 31. Xiaomi 32. Huawei
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 Chroma vs. Qdrant and other solutions. Updated: August 2026.
913,806 professionals have used our research since 2012.