ClickHouse vs DataStax Enterprise comparison

ClickHouse and IBM are both solutions in the Vector Databases category. ClickHouse is ranked #7 with an average rating of 8.6, while IBM is ranked #15 with an average rating of 8.0. ClickHouse holds a 5.1% mindshare in VD, compared to IBM’s 1.4% mindshare. Additionally, 100% of ClickHouse users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

ClickHouse

Read 21 ClickHouse reviews

4,435 Views
1,774 Comparison Views

100% willing to recommend

DataStax Enterprise

Read 1 DataStax Enterprise review

711 Views
398 Comparison Views

100% willing to recommend

ClickHouse

DataStax Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 1, 2026

DataStax Enterprise and ClickHouse are both top contenders in the database solutions category, each offering unique strengths. DataStax Enterprise is better for enterprises needing robust support and deployment flexibility, while ClickHouse is superior for high-speed data processing.

Features: DataStax Enterprise provides comprehensive scalability, robust security features, and supports mixed workloads, catering to organizations with diverse data handling needs. ClickHouse focuses on high-speed analytics, real-time data processing, and offers outstanding query performance, appealing primarily to analytics-driven users.

Ease of Deployment and Customer Service: DataStax Enterprise is recognized for easy deployment and excellent customer support, suiting complex enterprise environments with seamless integration and ongoing assistance. ClickHouse targets tech-savvy users with a self-service approach, offering deployment and maintenance flexibility for technically proficient users.

Pricing and ROI: DataStax Enterprise involves higher setup costs due to its enterprise-focused services but provides significant ROI for extensive support and robust database needs. ClickHouse's open-source model leads to lower initial costs, making it attractive for cost-effective analytics with quick returns due to its data processing efficiency.

To learn more, read our detailed Vector Databases Report (Updated: March 2026).

Buyer's Guide

Vector Databases

March 2026

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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

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)

DataStax Enterprise

Ranking in Vector Databases

15th

Average Rating

8.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

NoSQL Databases (14th)

Mindshare comparison

As of March 2026, in the Vector Databases category, the mindshare of ClickHouse is 5.1%, up from 2.9% compared to the previous year. The mindshare of DataStax Enterprise is 1.4%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
ClickHouse	5.1%
DataStax Enterprise	1.4%
Other	93.5%

Vector Databases

Featured Reviews

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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Suzanne Kimono

Senior Software Engineer at Deloitte

Continuous data access has ensured high uptime and has supported real-time transactional processing

The best features DataStax Enterprise offers include scaling, speed of data access, and ease of use for those familiar with traditional SQL. The scaling and speed of data access have benefited my team because the scaling and the speeding of data provide linear scale as well as multi-data centers' real-time replication of data such that we can maintain uptime even with the loss of multiple data centers. It enables us to maintain our uptime, which is very crucial for our clients. DataStax Enterprise has positively impacted my organization by providing the ability to have our services up and running even with a total outage at one of our data centers. There is no need to maintain windows since we can turn off data centers while doing maintenance and then put them back in the rotation and move on. I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great.

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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

"ClickHouse provides great query speeds because it is an OLAP database, so naturally, it provides higher speeds."

"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."

"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."

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

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

"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."

More ClickHouse pros

"I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great."

Cons

"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."

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

"ClickHouse could be improved further in several areas."

"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."

"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 could be improved with self-hosting capabilities and better documentation for how to host it at scale."

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

"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

"If not keeping current with updates, updating from an older major version to a newer major version can be a bit complicated and time-consuming, but DataStax Enterprise support will help us with this."

Pricing and Cost Advice

"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."

"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."

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

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

16%

Manufacturing Company

Educational Organization

Retailer

11%

Financial Services Firm

11%

Manufacturing Company

11%

Computer Software Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

No data available

Questions from the Community

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...

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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 ...

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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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What is your experience regarding pricing and costs for DataStax Enterprise?

My experience with pricing, setup cost, and licensing indicates that the cost is a bit affordable, especially for my organization. However, for smaller organizations working under a tight budget, i...

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What needs improvement with DataStax Enterprise?

I think DataStax Enterprise can be improved by having a hybrid on-prem and cloud solution with Astra. Better compatibility with prior versions in terms of codebases should also be improved. More wa...

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What is your primary use case for DataStax Enterprise?

DataStax Enterprise serves as the primary database for all transactional processing in my organization. DataStax Enterprise provides linear scale as well as multi-data center real-time replication ...

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Product Reports

Buyer's Guide

ClickHouse

March 2026

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Buyer's Guide

NoSQL Databases

March 2026

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Overview

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.

ClickHouse

DataStax Enterprise offers a high-performance, scalable database solution designed for modern data requirements, supporting a wide array of use cases that demand real-time analytics and robust security.

Focusing on delivering powerful distributed databases, DataStax Enterprise integrates the open-source foundation of Apache Cassandra, delivering enhanced features for enterprises. It supports mission-critical applications at scale, providing real-time query capabilities and fault tolerance. Designed with high availability and operational efficiency, it supports complex data models and simplifies management with advanced tools for monitoring and repair.

What are the standout features of DataStax Enterprise?

Advanced Security: Provides comprehensive data protection with encryption and identity management.
Graph Database Support: Allows complex data relationships to be easily modeled and queried.
Search Integration: Facilitates full-text search capabilities combined with Cassandra's strengths.
Analytics: Offers integrated analytics with Apache Spark for real-time data processing.
Multi-Cloud Support: Ensures easy deployment across different cloud environments without vendor lock-in.

What benefits should reviews highlight?

Scalability: Seamlessly expands to accommodate growing data volumes and user demands.
Performance: Maintains high-speed data processing even at massive scales.
Resilience: Provides high availability to ensure business continuity.
Cost Efficiency: Enables optimization of infrastructure investments with flexible deployments.

In industries such as finance, telecommunications, and retail, DataStax Enterprise is implemented to handle immense data workloads, often leveraging its capabilities for fraud detection, personalized customer experiences, and real-time decision-making. Its deployment in these sectors highlights its adaptability and performance in demanding environments.

IBM

Sample Customers

Information Not Available

ING, Netflix, UBS, eBay, Constant Contact, Aeris, Arise, ClearCapital, Dyn, Engine, Noble Group, Pantheon, Target

Find out what your peers are saying about Microsoft, Elastic, Redis and others in Vector Databases. Updated: March 2026.

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