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Chroma vs ClickHouse 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

Chroma
Ranking in Vector Databases
11th
Average Rating
8.6
Reviews Sentiment
5.6
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 (3rd)
 

Mindshare comparison

As of May 2026, in the Vector Databases category, the mindshare of Chroma is 7.1%, down from 13.0% compared to the previous year. The mindshare of ClickHouse is 5.6%, up from 3.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
ClickHouse5.6%
Chroma7.1%
Other87.3%
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…
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.

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 has positively impacted my organization by replacing PostgreSQL, which required complex foreign tables for queries, and with ClickHouse we now have Cube.js for easier data visualization."
"ClickHouse provides great query speeds because it is an OLAP database, so naturally, it provides higher speeds."
"We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case."
"ClickHouse is very easy to use; one of the good features is that it has joins, which were not present in Druid, and Druid was quite expensive, especially with our applications at Sam's Club utilizing ClickHouse very quickly."
"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."
"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."
"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 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."
 

Cons

"I think Chroma doesn't have a ready-made containerized image available."
"The hybrid algorithm needs improvement."
"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."
"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."
"We would like to have fuzzy search capabilities in ClickHouse like we had with Kibana because there are scenarios where we cannot search keywords fuzzily in ClickHouse, whereas Elasticsearch allows that, and in such cases, Elasticsearch outperforms ClickHouse."
"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 main issue is the lack of documentation. Many features are available but are not fully documented, which can make finding information challenging."
"ClickHouse could be improved with self-hosting capabilities and better documentation for how to host it at scale."
"I would like ClickHouse to work more on integration with third-party tools."
"The aggregation capability is a valuable feature. It's highly efficient, allowing us to review entire transaction histories and user activities in the market. We've tried MongoDB, Postgres, MariaDB, and BigQuery, but ClickHouse is the most cost-efficient solution for collecting data at high speeds with minimal cost. We even used ClickHouse Cloud for a month, and it proved to be a great setup, especially for startups looking to handle big data. For example, if there is a need for 2-4 terabytes of data and around 40 billion rows with reasonable computing speed and latency, ClickHouse is ideal. Regarding the real-time query performance of ClickHouse, when using an API server to query it, I achieved query results in less than twenty milliseconds in some of my experiments with one billion rows. However, it depends on the scenario since ClickHouse has limitations in handling mutations. Additionally, one of ClickHouse's strengths is its compression capability. Our experimental server has only four terabytes, and ClickHouse effectively compresses data, allowing us to store large amounts of data at high speed. This compression efficiency is a significant advantage of using ClickHouse."
 

Pricing and Cost Advice

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

By visitors reading reviews
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
9%
Government
8%
Financial Services Firm
16%
Computer Software Company
14%
Comms Service Provider
9%
Outsourcing Company
8%
 

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: April 2026.
893,244 professionals have used our research since 2012.