Cassandra vs ClickHouse comparison

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Cassandra

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Executive SummaryUpdated on Mar 1, 2026

Apache Cassandra and ClickHouse are open-source database management systems. ClickHouse appears to have an advantage due to its superior analytical capabilities, although Cassandra offers excellent value and support.

Features: Cassandra provides peer-to-peer architecture, distributed scalability, and high availability. ClickHouse benefits from a columnar storage system, real-time queries, and efficient data compression.

Room for Improvement: Cassandra could improve in query performance and user interface friendliness, as well as providing more comprehensive query language support. ClickHouse could be enhanced in handling transactional workloads, simplifying integration with other systems, and better managing very high concurrency.

Ease of Deployment and Customer Service: Cassandra involves more complexity in setup and requires significant expertise, whereas ClickHouse benefits from simpler installation and a responsive community-driven support system, making deployment smoother.

Pricing and ROI: Cassandra is usually lower in initial costs and delivers high ROI with large datasets. ClickHouse may involve higher setup costs but offers significant performance benefits for analytical tasks, leading to a high return on analytical investments.

To learn more, read our detailed Cassandra vs. ClickHouse Report (Updated: September 2026).

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Cassandra vs. ClickHouse

September 2026

Helped 917,181 peers since 2012

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

12th

Average Rating

8.0

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

NoSQL Databases (5th)

ClickHouse

Ranking in Vector Databases

8th

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Open Source Databases (3rd)

Mindshare comparison

As of October 2026, in the Vector Databases category, the mindshare of Cassandra is 4.0%, up from 2.0% compared to the previous year. The mindshare of ClickHouse is 5.8%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
ClickHouse	5.8%
Cassandra	4.0%
Other	90.2%

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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reviewer2785038

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.

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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

"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."

"The solution's database capabilities are very good."

"Ability to achieve write speeds 10k tps: Compared to existing, it is 300% percent higher."

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

"I am satisfied with the performance; so far it has done fairly well and there haven't been any complaints."

"We have experienced zero downtime using Cassandra, it is highly stable."

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

"Setup was very straightforward."

More Cassandra pros

"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."

"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."

"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."

"The tool is column-based and infinitely scalable."

"ClickHouse has reduced our storage cost and improved our 99th percentile latency by 40%."

"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."

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

"We moved away from Redshift to ClickHouse because of the integration and the flexibility that it provides, which best suited our use case."

More ClickHouse pros

Cons

"We have had stability issues including out of memory issues and crashes with earlier versions of the product."

"Cassandra can improve by adding more built-in tools. For example, if you want to do some maintenance activities in the cluster, we have to depend on third-party tools. Having these tools build-in would be e benefit."

"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."

"We experience configuration issues when accommodating the volumes we require, which often necessitates consultation with the Cassandra development team."

"Interface is not user friendly."

"If you have a requirement of aggregation and joints, Cassandra doesn't support a solution that can give the aggregation."

"The interface could definitely be improved. It's a technical database and for me the features are not user friendly."

More Cassandra cons

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

"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."

"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."

"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."

"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."

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

"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."

More ClickHouse cons

Pricing and Cost Advice

"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."

"We pay for a license."

"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 used the free, community version of ClickHouse."

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

"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."

"The tool is open-source."

"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

15%

Comms Service Provider

10%

Construction Company

Outsourcing Company

Financial Services Firm

16%

Computer Software Company

11%

Outsourcing Company

10%

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	2
Large Enterprise	14

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	8

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...

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Compared 6% of the time

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Compared 6% of the time

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Product Reports

Download Cassandra product report

Cassandra

October 2026

Download ClickHouse product report

October 2026

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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