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: June 2025).

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Cassandra vs. ClickHouse

June 2025

Helped 861,524 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

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."

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

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

"The most valuable features are the counter features and the NoSQL schema. It also has good scalability. You can scale Cassandra to any finite level."

"Its retrieval is similar to an RDBMS, so our team finds it easy to adapt."

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

"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."

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

More Cassandra pros

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

"The main feature of ClickHouse is the optimizer because we had too many records to deduplicate, and the optimizer took this task by itself."

"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."

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

"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."

"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."

"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."

More ClickHouse pros

Cons

"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."

"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."

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

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

"The initial setup of Cassandra can be difficult in the configuration. There might be a need to have assistance. The implementation process can six months for connecting to certain databases."

"The solution doesn't have joins between tables so you need other tools for that."

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

"I want Cassandra to update its open-source version more quickly. It's already feature-rich, but I'd appreciate better integration with other NoSQL databases like MariaDB or MongoDB. If I ever need to work with customers or vendors using different NoSQL databases, having native integration in Cassandra would make managing and interacting with their databases much easier."

More Cassandra cons

"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."

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

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

"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."

"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."

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

More ClickHouse cons

Pricing and Cost Advice

"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."

"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."

"We pay for a license."

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

"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."

"The tool is free."

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

"The tool is open-source."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

14%

Comms Service Provider

Retailer

Computer Software Company

24%

Financial Services Firm

16%

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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Comparisons

MongoDB vs Cassandra

Compared 14% of the time

Couchbase vs Cassandra

Compared 13% of the time

ScyllaDB vs Cassandra

Compared 8% of the time

Chroma vs Cassandra

Compared 7% of the time

InfluxDB vs Cassandra

Compared 7% of the time

InfluxDB vs ClickHouse

Compared 23% of the time

OpenSearch vs ClickHouse

Compared 11% of the time

SingleStore vs ClickHouse

Compared 10% of the time

Milvus vs ClickHouse

Compared 8% of the time

Redis vs ClickHouse

Compared 6% of the time

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Product Reports

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Cassandra

July 2025

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July 2025

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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