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Cassandra 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

Cassandra
Ranking in Vector Databases
14th
Average Rating
8.0
Reviews Sentiment
6.0
Number of Reviews
25
Ranking in other categories
NoSQL Databases (7th)
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 April 2026, in the Vector Databases category, the mindshare of Cassandra is 2.6%, up from 1.7% compared to the previous year. The mindshare of ClickHouse is 5.1%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Vector Databases Mindshare Distribution
ProductMindshare (%)
ClickHouse5.1%
Cassandra2.6%
Other92.3%
Vector Databases
 

Featured Reviews

Monirul Islam Khan - PeerSpot reviewer
Head, Data Integration & Management at a non-profit with 10,001+ employees
Has maintained secure document storage and efficient data distribution with peer-to-peer architecture
The functions or features in Cassandra that I have found most valuable are that it is a distributed system similar to Mongo. It's good enough for comparison with another SQL database, so it's smooth and organized for distributed database system. The peer-to-peer architecture in Cassandra is helpful for network decentralization, and I have already introduced that feature. Cassandra features in peer-to-peer as well as another monitoring, so basically, it's good enough for our service. The tunable consistency level in Cassandra is good, and we are using that feature already. In terms of built-in caching and lightweight transactions in Cassandra, the transaction level is good, and it's optimized, so there are no more issues in that database. Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there. Additionally, the database monitoring system or auditing system is well-comparable with other database systems, so we are actually happy to be using this Cassandra database.
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 provided us with more than 100K PNRs a second and because the company was international there was a heavy data write, and at the same time a heavy data read."
"Our primary use case for the solution is testing."
"I am satisfied with the performance."
"Ability to achieve write speeds 10k tps: Compared to existing, it is 300% percent higher."
"I am getting much better performance than relational databases."
"I'd rate the solution ten out of ten."
"Setup was very straightforward."
"Cassandra is good. It's better than CouchDB, and we are using it in parallel with CouchDB. Cassandra looks better and is more user-friendly."
"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."
"We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case."
"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."
"There is no better option than ClickHouse in all OLAP-based databases, so I think it is best to use ClickHouse in that regard."
"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 a user-friendly solution that tries to be compatible with SQL standards."
"ClickHouse has positively impacted my organization, as there was an entire exercise done on which database we were supposed to use for solving our problems, and we found ClickHouse was the one performing the best, which is when we adopted it."
"ClickHouse provides responses within a few seconds, typically two to three seconds, which is impressive."
 

Cons

"Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProxy, which should better handle consumption for high-level concurrency."
"The interface could definitely be improved. It's a technical database and for me the features are not user friendly."
"The solution is limited to a linear performance."
"Maybe they can improve their performance in data fetching from a high volume of data sets."
"The solution is not easy to use because it is a big database and you have to learn the interface."
"We have had stability issues including out of memory issues and crashes with earlier versions of the product."
"While Cassandra can handle NoSQL, I think there should be more flexibility for whole schema design when data is stored in wide columns. Additionally, I believe that eventual consistency should be enhanced."
"The clustering needs to be better; it is getting there."
"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 could be improved with self-hosting capabilities and better documentation for how to host it at scale."
"ClickHouse could be improved further in several areas."
"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."
"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."
"ClickHouse can be improved, and the main challenge I see is its operational complexity."
"We had a lot of troubles while deploying a whole cluster."
"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

"I use the tool's open-source version."
"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."
"We are using the open-source version of Cassandra, the solution is free."
"Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise."
"I don't have the specific numbers on pricing, but it was fairly priced."
"We pay for a license."
"The tool is free."
"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."
"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."
"The tool is open-source."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
7%
Retailer
7%
Comms Service Provider
7%
Financial Services Firm
16%
Computer Software Company
15%
Outsourcing Company
8%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise14
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise4
Large Enterprise8
 

Questions from the Community

What is your experience regarding pricing and costs for Cassandra?
The pricing for Cassandra is a little bit high, so it would be better for our community services if they consider community pricing for any non-profit organization like an NGO or other things. It w...
What needs improvement with Cassandra?
Regarding areas of improvement for Cassandra, currently, we are not facing significant issues. Some issues arise from our vendors like Apache slowness and distribution or load balancing from HAProx...
What is your primary use case for Cassandra?
My use case for Cassandra is for a document and other unstructured data management system as well as structured data for ultra-poor member community edition, community members' PII information, so ...
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. Apple 2. Netflix 3. Facebook 4. Instagram 5. Twitter 6. eBay 7. Spotify 8. Uber 9. Airbnb 10. Adobe 11. Cisco 12. IBM 13. Microsoft 14. Yahoo 15. Reddit 16. Pinterest 17. Salesforce 18. LinkedIn 19. Hulu 20. Airbnb 21. Walmart 22. Target 23. Sony 24. Intel 25. Cisco 26. HP 27. Oracle 28. SAP 29. GE 30. Siemens 31. Volkswagen 32. Toyota
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Find out what your peers are saying about Cassandra vs. ClickHouse and other solutions. Updated: February 2026.
885,444 professionals have used our research since 2012.