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Chroma vs ClickHouse comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 23, 2025

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
10th
Average Rating
8.6
Reviews Sentiment
5.5
Number of Reviews
2
Ranking in other categories
No ranking in other categories
ClickHouse
Ranking in Vector Databases
7th
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
21
Ranking in other categories
Open Source Databases (4th)
 

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of Chroma is 8.9%, down from 14.4% compared to the previous year. The mindshare of ClickHouse is 4.9%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Market Share Distribution
ProductMarket Share (%)
ClickHouse4.9%
Chroma8.9%
Other86.2%
Vector Databases
 

Featured Reviews

Sameer Bhangale - PeerSpot reviewer
Leader, Data Science Practice at a computer software company with 5,001-10,000 employees
Used for RAG (Retrieval-augmented generation) and provides good documentation
If I have to deploy my application in a scalable environment with lots of data and users, I sometimes need to create multiple instances of my database or have a distributed database across different machines. Using Kubernetes, I can quickly increase the horizontal spread of Milvus because it is containerized and readily available. I don't have to do anything by myself. New users can go to Chroma's 'Get Started' page and follow it like a tutorial. Then, they will be ready to use the solution. Chroma has helped us reduce the overall project post production time. Overall, I rate the solution an eight out of ten.
Yush Mittal - PeerSpot reviewer
Level 2 Software Engineer at a computer software company with 201-500 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.

Quotes from Members

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

Pros

"The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it."
"It's very easy to set up and runs easily."
"ClickHouse is open source with no vendor lock-in, providing excellent freedom to choose any vendor without restrictions."
"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."
"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."
"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."
"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 provides responses within a few seconds, typically two to three seconds, which is impressive."
"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."
"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."
 

Cons

"I think Chroma doesn't have a ready-made containerized image available."
"The hybrid algorithm needs improvement."
"We had a lot of troubles while deploying a whole cluster."
"I chose nine out of ten because, as I mentioned, the improvement side and the ten thousand partition limit created issues that we were hitting quite frequently, but with some schema manipulations we did manage to find a workaround, although that could have been avoided had things been better documented on how we could have solved this problem in a different approach, which took some bandwidth."
"The open-source version of ClickHouse is not very scalable."
"ClickHouse could be improved further in several areas."
"ClickHouse could be improved with self-hosting capabilities and better documentation for how to host it at scale."
"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."
"Initially, I faced challenges integrating ClickHouse, particularly with inserting data from ActiveMQ, which caused duplicates. However, after adjusting the ClickHouse settings, the issue was resolved and there were no more duplicates."
"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."
 

Pricing and Cost Advice

"The current version is an open-source."
"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."
"We used the free, community version of ClickHouse."
"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."
"The tool is open-source."
"ClickHouse has an open-source version, which is free to use and has almost all the features."
"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."
"The tool is free."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
University
8%
Financial Services Firm
17%
Computer Software Company
16%
Manufacturing Company
8%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise4
Large Enterprise8
 

Questions from the Community

What do you like most about Chroma?
The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it.
What needs improvement with Chroma?
The hybrid algorithm needs improvement.
What is your primary use case for Chroma?
We collect customer's feedback, and then we present it to the clients.
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...
 

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
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Find out what your peers are saying about Chroma vs. ClickHouse and other solutions. Updated: December 2025.
881,707 professionals have used our research since 2012.