Cassandra vs ClickHouse comparison

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Cassandra

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Executive SummaryUpdated on Mar 5, 2025

Cassandra and ClickHouse are major players in the database management domain, each excelling in different areas of data handling. While Cassandra excels in handling vast data volumes with its superior horizontal scalability, ClickHouse leads with its high-performance analytics and cost efficiencies for businesses seeking rapid insights.

Features: Cassandra's distributed architecture provides high availability, fault tolerance, and is suitable for real-time transactional workloads in multiple data centers. ClickHouse, with its efficient columnar storage, offers superior fast data retrieval and analytics processing for analytical workloads.

Room for Improvement: Cassandra could enhance its read performance and simplify its initial setup to be more user-friendly for new adopters. Improving documentation and reducing operational complexities are other areas for growth. ClickHouse may improve its support for complex data mutations and provide more comprehensive real-time streaming solutions. The need for expanded community documentation and simplified integration with various data ecosystems are possible enhancements.

Ease of Deployment and Customer Service: Cassandra's flexible deployment options are supported by extensive community resources, though initial configuration can be complex. ClickHouse offers simpler deployment models with robust cloud support, featuring customer service aligned with its straightforward setup procedures.

Pricing and ROI: Cassandra, with higher setup and operational costs, offers good ROI where high availability and write-heavy workloads are prioritized. In contrast, ClickHouse provides a cost-effective solution with a lower initial investment, enhancing ROI for data-driven businesses due to its performance and speed.

To learn more, read our detailed Cassandra vs. ClickHouse Report (Updated: July 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

6.1

Number of Reviews

Ranking in other categories

NoSQL Databases (6th)

ClickHouse

Ranking in Vector Databases

11th

Average Rating

8.8

Reviews Sentiment

7.8

Number of Reviews

Ranking in other categories

Open Source Databases (6th)

Mindshare comparison

As of July 2025, in the Vector Databases category, the mindshare of Cassandra is 1.8%, down from 1.9% compared to the previous year. The mindshare of ClickHouse is 3.8%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases

Featured Reviews

Himanshu Amodwala

Senior cloud solution architect at Microsoft

Well-equipped to handle a massive influx of data and billions of requests

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-time updates is paramount. For instance, when a customer leaves comments or feedback on an image, they anticipate an immediate reflection of these changes on the portal. Similarly, sellers altering product attributes or updating images expect instant visibility of these modifications. Handling large data volumes with Cassandra has been an excellent experience. Despite challenges related to the influx, these were not attributed to Cassandra itself but rather to middle-layer issues. Generally, it demonstrated scalability with workloads, thanks to its horizontal scaling capabilities. We could easily add new nodes to the system as needed, ensuring the platform coped well with increasing loads. The tool's most beneficial feature for scalability is its entire architecture. The absence of a single point of failure or a leader within the ecosystem contributes to its robust scalability. This key aspect influenced our decision to opt for the Cassandra ecosystem. In terms of performance, it demonstrated the ability to handle approximately 1.6 billion requests per day. This was achieved on AWS using EC2 instances, and it was during a period about four to five years ago.

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Aswini Atibudhi

Distinguished AI Leader at Walmart Global Tech at Walmart

Provides real-time data insights with high flexibility and responsive support

The basic challenge for ClickHouse is the documentation, which isn't ideal, but it's mature and stable with more columnar storage, compression, and parallel processing, making it the best for OLAP. 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.

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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

"Our primary use case for the solution is testing."

"The most valuable features of Cassandra are the NoSQL database, high performance, and zero-copy streaming."

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

"Some of the valued features of this solution are it has good performance and failover."

"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-time updates is paramount."

"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."

"I am satisfied with the performance."

"A consistent solution."

More Cassandra pros

"We faced a challenge with deploying ClickHouse onto Kubernetes. Recently, we've been using ClickHouse Cloud, and the main issue is the high cost of the cloud service. The pricing isn't very competitive, especially for startups. I would instead buy a server and self-host if I have enough disk space. Besides that, ClickHouse has done very well, with clear goals and effective execution."

"It's easier to work with big data and calculations using the product."

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

"ClickHouse is open source with no vendor lock-in, providing excellent freedom to choose any vendor without restrictions."

"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."

"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 tool is column-based and infinitely scalable."

"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."

More ClickHouse pros

Cons

"There were challenges with the query language and the development interface. The query language, in particular, could be improved for better optimization. These challenges were encountered while using the Java SDK."

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

"Doesn't support a solution that can give aggregation."

"Batching bulk data can cause performance issues."

"Fine-tuning was a bit of a challenge."

"The secondary index in Cassandra was a bit problematic and could be improved."

"Interface is not user friendly."

"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

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

"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."

"One issue is that you need persistent volumes. Otherwise, if one system goes down, you lose data in that cluster."

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

"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."

"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."

"The main issue is the lack of documentation. Many features are available but are not fully documented, which can make finding information challenging."

More ClickHouse cons

Pricing and Cost Advice

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

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

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

"We pay for a license."

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

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

"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 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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

13%

Comms Service Provider

Retailer

Computer Software Company

23%

Financial Services Firm

17%

Educational Organization

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Cassandra?

What is your experience regarding pricing and costs for Cassandra?

We are using Cassandra locally and as open-source.

What needs improvement with Cassandra?

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 e...

What is your experience regarding pricing and costs for ClickHouse?

ClickHouse is open source without direct fees, unlike other databases that have hidden fees or restrict hosting to their platforms. The open-source nature of ClickHouse allows for complete flexibil...

What needs improvement with ClickHouse?

What is your primary use case for ClickHouse?

I have experience in ClickHouse ( /products/clickhouse-reviews ), and we also use Apache Druid ( /products/druid-reviews ), which has corporate support from Druid ( /products/druid-reviews ), along...

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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