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: April 2026).

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Cassandra vs. ClickHouse

April 2026

Helped 896,803 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 (6th)

ClickHouse

Ranking in Vector Databases

7th

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Open Source Databases (3rd)

Mindshare comparison

As of June 2026, in the Vector Databases category, the mindshare of Cassandra is 3.5%, up from 1.9% compared to the previous year. The mindshare of ClickHouse is 5.6%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
ClickHouse	5.6%
Cassandra	3.5%
Other	90.9%

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

"We can add almost one million columns to the solution."

"Since I haven't had years of experience with it, it's still new to me. One valuable feature is its distribution, so I can run it partly in the cloud and part on-prem. That's a feature I'd like to use but haven't yet because we're trying to move to Azure. I don't know if or when that will happen. Ideally, we'd have it distributed over the cloud and on-prem simultaneously, so if something happens to our on-prem, we can keep going in the cloud, like a pay-as-you-go model with Azure."

"The technical evaluation is very good."

"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."

"Cassandra is good, it's better than CouchDB, and we are using it in parallel with CouchDB, as Cassandra looks better and is more user-friendly."

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

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

"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."

More Cassandra pros

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

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

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

"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."

"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 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 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."

More ClickHouse pros

Cons

"Interface is not user friendly."

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

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

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

"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."

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

"The disc space is lacking. You need to free it up as you are working."

More Cassandra cons

"In terms of needed improvements, some enhancements in documentation are necessary."

"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."

"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."

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

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

"I chose nine out of ten because, as I mentioned, the improvement side and the ten thousand partition limit created issues that we were hitting quite frequently, but with some schema manipulations we did manage to find a workaround, although that could have been avoided had things been better documented on how we could have solved this problem in a different approach, which took some bandwidth."

"We would like to have fuzzy search capabilities in ClickHouse like we had with Kibana because there are scenarios where we cannot search keywords fuzzily in ClickHouse, whereas Elasticsearch allows that, and in such cases, Elasticsearch outperforms ClickHouse."

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."

"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."

"We pay for a license."

"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."

"The tool is free."

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

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

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

"The tool is open-source."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Comms Service Provider

Computer Software Company

Performing Arts

Financial Services Firm

16%

Computer Software Company

14%

Outsourcing Company

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...

MongoDB Enterprise Advanced vs Cassandra

Comparisons

Compared 8% of the time

ScyllaDB vs Cassandra

Compared 5% of the time

DataStax Enterprise vs Cassandra

Compared 5% of the time

Cloudera Distribution for Hadoop vs Cassandra

Compared 5% of the time

Couchbase Enterprise vs Cassandra

Compared 5% of the time

More Cassandra Competitors

OpenSearch vs ClickHouse

Compared 10% of the time

MySQL vs ClickHouse

Compared 7% of the time

VictoriaMetrics vs ClickHouse

Compared 7% of the time

InfluxDB vs ClickHouse

Compared 7% of the time

PostgreSQL vs ClickHouse

Compared 6% of the time

More ClickHouse Competitors

Product Reports

Download Cassandra product report

Cassandra

May 2026

Download ClickHouse product report

May 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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