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ClickHouse vs Qdrant comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 1, 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

ClickHouse
Ranking in Open Source Databases
3rd
Ranking in Vector Databases
7th
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
21
Ranking in other categories
No ranking in other categories
Qdrant
Ranking in Open Source Databases
11th
Ranking in Vector Databases
4th
Average Rating
9.0
Reviews Sentiment
4.8
Number of Reviews
2
Ranking in other categories
AI Data Analysis (17th)
 

Mindshare comparison

As of March 2026, in the Open Source Databases category, the mindshare of ClickHouse is 6.6%, up from 2.8% compared to the previous year. The mindshare of Qdrant is 4.2%, up from 3.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Open Source Databases Mindshare Distribution
ProductMindshare (%)
ClickHouse6.6%
Qdrant4.2%
Other89.2%
Open Source Databases
 

Featured Reviews

reviewer2785038 - PeerSpot reviewer
Senior Data Engineer at a transportation company with 501-1,000 employees
Data observability has enabled real‑time analytics and cost savings but needs smoother inserts and cleanup
ClickHouse could be improved concerning data insertion, especially given the high amount of data handled. Constant efforts are made to optimize the features on its own, but with merges and inserts, only a single insert query can be performed allowing for the input of only 100,000 rows per second. It would be beneficial to insert more data and have configurations that are less user-operated. Ideally, ClickHouse would optimize itself to handle these processes automatically, reducing the need to contact the ClickHouse support team for infrastructure optimization. Additionally, delays are experienced when trying to delete databases with corrupt data, taking too much time and causing major outages, which necessitate contacting multiple teams across continents for resolution. The community surrounding ClickHouse also seems limited, providing a reliance on documentation, and there is a scarcity of developers working with ClickHouse, which hinders growth. If ClickHouse were more user-friendly and technically feasible, it would likely see greater expansion in usage.
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.

Quotes from Members

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

Pros

"With ClickHouse, since data is stored in a columnar way, we get aggregation functions that are much faster than transactional databases, such as SQL Server, and the cost efficiency is also much reduced compared to Cosmos DB since we use it on-premises, the cost is nearly cut, which is very useful for us."
"ClickHouse provides great query speeds because it is an OLAP database, so naturally, it provides higher speeds."
"The best thing about the tool is that I can set it up on my computer and run queries without depending on the cloud. This is why I use it every day."
"ClickHouse is much faster than traditional databases like MySQL and MongoDB. Its column-row searching strategy makes it very efficient. With ClickHouse, we can manage multiple databases, automatically insert data from other databases and delete data as needed. It supports real-time query performance, allowing simultaneous data insertion and retrieval. ClickHouse has improved significantly over the past two years, adding more functions and queries, as well as top functionality."
"Regarding performance, we tried multiple solutions when Kibana was failing, including PostgreSQL, MySQL, and even MongoDB for log ingestion of huge volumes, but ClickHouse outperformed all databases we tested, leading us to choose it for further use cases."
"ClickHouse is open source with no vendor lock-in, providing excellent freedom to choose any vendor without restrictions."
"We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case."
"If you have a real-time basis, you should take a look at ClickHouse because it works on a vector database, and the querying is super fast compared to traditional databases."
"Using Qdrant's hybrid search capability has improved my search results."
"Due to its quantization ability, we were able to store the same amount of data in less space, which reduced our cloud bills by 30%."
"Due to its quantization ability, we were able to store the same amount of data in less space, which reduced our cloud bills by 30%."
 

Cons

"There are some areas where ClickHouse could improve. Specifically, we encountered incompatibilities with its SQL syntax when migrating queries from MySQL or SQL to ClickHouse. This difference in details made it challenging to figure out the exact issues. Additionally, we faced difficulties due to the lack of a proper Django driver for ClickHouse, unlike MySQL, which Django supports out of the box."
"I would like ClickHouse to work more on integration with third-party tools."
"If you join our team, it should be easy for you to use ClickHouse, especially if you are a developer. However, you need to read the documentation and understand the problems you are trying to solve."
"ClickHouse can be improved, and the main challenge I see is its operational complexity."
"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."
"In terms of improvements, it's not designed for very frequent small writes, making it less scalable in write-intensive workloads, and it's not flourishing in transactional use cases or when ingesting streaming data, such as batching or buffering, which is something ClickHouse will improve."
"In terms of needed improvements, some enhancements in documentation are necessary."
"We had a lot of troubles while deploying a whole cluster."
"Qdrant can be improved in several ways."
"Qdrant can be improved in several ways."
 

Pricing and Cost Advice

"The tool is free."
"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."
"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."
"For pricing, if you use the self-hosted version, it would be free. Cloud services pricing would be an eight out of ten. I try to minimize costs but still have to monitor usage."
"ClickHouse has an open-source version, which is free to use and has almost all the features."
"The tool is open-source."
"We used the free, community version of ClickHouse."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
16%
Manufacturing Company
8%
Educational Organization
7%
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
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise4
Large Enterprise8
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ClickHouse?
My experience with pricing, setup cost, and licensing was such that the setup costs were just my own bandwidth, while licensing and pricing were done by other members of the team so it was abstract...
What needs improvement with ClickHouse?
ClickHouse can be improved on the documentation side, and there is one small constraint that is mentioned in ClickHouse documentation, which is a partition limit of ten thousand that we hit, so if ...
What is your primary use case for ClickHouse?
My main use case for ClickHouse is data ingestion and for its OLAP properties, as we had use cases where database locks were slowing us down and because ClickHouse does not have that, we chose to u...
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.
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
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 Oracle, PostgreSQL, ClickHouse and others in Open Source Databases. Updated: February 2026.
884,797 professionals have used our research since 2012.