Cassandra vs ClickHouse comparison

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Cassandra

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Executive SummaryUpdated on Nov 23, 2025

Cassandra and ClickHouse compete in the database management system category. Based on performance and features, ClickHouse often holds the upper hand due to its exceptional speed and analytical capabilities.

Features: Cassandra offers scalability, fault tolerance, and a distributed architecture that excels at managing large datasets. ClickHouse provides high-speed query performance, advanced analytics, and real-time data processing, making it ideal for analytics-heavy tasks.

Room for Improvement: Cassandra may face challenges with read performance and requires improvements in data consistency tuning. It could enhance its documentation for better user adoption. ClickHouse can improve in handling data mutations and easing initial setup complexity. Its integration with other systems could be further optimized.

Ease of Deployment and Customer Service: Cassandra's straightforward deployment process is supported by a robust technical community, ensuring efficient problem-solving. ClickHouse requires more technical expertise upon deployment but offers extensive documentation and effective support channels, rewarding with superior performance.

Pricing and ROI: Cassandra is cost-effective with a modest initial setup and offers great ROI for startups due to its open-source nature. ClickHouse has a higher initial cost due to advanced hardware needs but delivers significant ROI through superior query performance and efficiency for complex analytics.

To learn more, read our detailed Cassandra vs. ClickHouse Report (Updated: December 2025).

Cassandra vs. ClickHouse

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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

Ranking in other categories

NoSQL Databases (6th)

ClickHouse

Ranking in Vector Databases

9th

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Open Source Databases (6th)

Mindshare comparison

As of December 2025, in the Vector Databases category, the mindshare of Cassandra is 2.1%, up from 1.6% compared to the previous year. The mindshare of ClickHouse is 4.4%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
ClickHouse	4.4%
Cassandra	2.1%
Other	93.5%

Vector Databases

Featured Reviews

Monirul Islam Khan

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.

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Yush Mittal

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.

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Quotes from Members

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

Pros

"Can achieve continuous data without a single downtime because of node to node ring architecture."

"I am satisfied with the performance."

"I'd rate the solution ten out of ten."

"Based on my experience, Cassandra is good for document management system, as well as distributed database system, and the automatic recovery process is there."

"The time series data was one of the best features along with auto publishing."

"Overall, I would rate Cassandra as nine because of its fast writes, which really suit our use cases mostly."

"The most valuable feature of Cassandra is its fast retrieval. Additionally, the solution can handle large amounts of data. It is the quickest application we use."

"Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now."

More Cassandra 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 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."

"ClickHouse Cloud saves a lot of time for our DevOps engineers since there isn't much deployment involved and everything is served directly, leading to increased efficiency and productivity."

"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."

"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."

"ClickHouse provides responses within a few seconds, typically two to three seconds, which is impressive."

"ClickHouse has positively impacted our organization by optimizing costs and significantly reducing latencies, which has improved customer experience greatly."

More ClickHouse pros

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."

"There could be more integration, and it could be more user-friendly."

"Cassandra could be more user-friendly like MongoDB."

"Interface is not user friendly."

"Cassandra is very complex to manage. Sometimes, I need to involve a senior DevOps engineer if we encounter a problem."

"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."

"It can be difficult to analyze what's going on inside of the database relative to other databases. It can also be difficult to troubleshoot sometimes."

"The solution is not easy to use because it is a big database and you have to learn the interface. This is the case though in most of these solutions."

More Cassandra cons

"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."

"The open-source version of ClickHouse is not very scalable."

"There aren't too many improvements I'd suggest for ClickHouse as it covers all my needs. There are just a few technical issues. For example, sometimes, when you want to get unique values and use certain tables, they don't work as expected. But it's not a major problem."

"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."

"ClickHouse can be improved, and the main challenge I see is its operational complexity."

"My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option."

"We had a lot of troubles while deploying a whole cluster."

"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."

More ClickHouse cons

Pricing and Cost Advice

"I don't have the specific numbers on pricing, but it was fairly priced."

"Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise."

"We pay for a license."

"We are using the open-source version of Cassandra, the solution is free."

"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."

"I use the tool's open-source version."

"ClickHouse has an open-source version, which is free to use and has almost all the features."

"We used the free, community version of ClickHouse."

"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."

"The tool is free."

"The tool is open-source."

"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."

"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

Retailer

Comms Service Provider

Financial Services Firm

17%

Computer Software Company

17%

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	1
Large Enterprise	14

By reviewers
Company Size	Count
Small Business	13
Midsize Enterprise	4
Large Enterprise	8

Questions from the Community

What do you like most about Cassandra?

The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-ti...

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 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...

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Product Reports

Cassandra

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Overview

Cassandra is a distributed and scalable database management system used for real-time data processing.

It is highly valued for its ability to handle large amounts of data, scalability, high availability, fault tolerance, and flexible data model.

It is commonly used in finance, e-commerce, and social media industries.

Apache

ClickHouse is renowned for its speed, scalability, and real-time query performance. Its compatibility with SQL standards enhances flexibility while enabling integration with popular tools.

ClickHouse leverages a column-based architecture for efficient data compression and real-time analytics. It seamlessly integrates with tools like Kafka and Tableau and is effective in handling large datasets due to its cost-efficient aggregation capabilities. With robust data deduplication and strong community backing, users can access comprehensive documentation and up-to-date functionality. However, improvements in third-party integration, cloud deployment, and handling of SQL syntax differences are noted, impacting ease-of-use and migration from other databases.

What features make ClickHouse outstanding?

Speed and Scalability: Enables rapid deployment and scalability, particularly on Kubernetes.
SQL Compatibility: Aligns with SQL standards for flexible database management.
Column-based Structure: Offers efficient data compression and quick query performance.
Integration Support: Works with Kafka, Tableau, and other popular platforms.
Data Deduplication: Manages complex data duplication efficiently.

What benefits should users consider?

Cost-Efficiency: Reduces expenses while managing large datasets effectively.
Real-Time Analytics: Provides fast data processing for real-time insights.
Flexibility: Offers multiple integration points and compatibility options.
Robust Documentation: Backed by an active development community, ensuring comprehensive support.

ClickHouse is deployed in sectors like telecommunications for passive monitoring and is beneficial for data analytics, logging Clickstream data, and as an ETL engine. Organizations harness it for machine learning applications when combined with GPT. With the ability to be installed independently, it's an attractive option for avoiding cloud service costs.

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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Cassandra vs. ClickHouse