

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.
I estimate we save four to five hours per person per week due to this efficiency, translating to around 20 to 25 hours saved monthly for each individual.
We could reduce the amount of employees needed when we migrated to ClickHouse Cloud.
With ClickHouse, we didn't need to spend much on resources, cutting costs by around 25 to 30%.
We have seen a return on investment with DataStax Enterprise as we saved a lot of money and time, despite investing more on infrastructure; our ongoing business success with a 99.9% uptime helps us earn more.
Earlier it was around 15 months, and we have been able to deploy and scale our application within 10 months.
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.
If more timely support could be provided during critical issues, situations could have been resolved much more quickly, saving considerable time.
When we faced any challenges, the ClickHouse support team provided helpful resolutions.
We utilize AVN ClickHouse, which is effectively managed by AVN, providing bug fixes and developing new functionalities along with architecture reviews.
Real-time transaction processing, both reads and writes, is where DataStax Enterprise shines the most.
I would rate the customer support nine out of 10.
one of my colleagues contacted them and found it to be pretty efficient
The vertical scalability is impressive, with high insert throughput, allowing millions of rows per second with low latency.
ClickHouse is highly scalable.
The scalability of ClickHouse is great.
DataStax Enterprise's scalability is very fast with linear scalability and hence is very scalable.
The active-active architecture helped us really scale and provide data to both Singapore and Indian users.
It auto-scales, and as user demands increase, we can gather more compute resources from the cloud and speed up the servers.
I can confidently say that it is very consistent and stable even when handling high volume loads and real-time streaming analytics across financial and operational domains.
ClickHouse handles large volumes of data efficiently.
ClickHouse is stable, as we did not encounter stability issues in production.
DataStax Enterprise provides enough stability for our organization, and scaling can be done up to terabytes and petabytes.
Another challenge is the lack of robust support for transactional databases, which limits its use as a primary database.
ClickHouse should be able to import data from other types of sources like Parquet and Iceberg tables and all the new upcoming data formats.
My experience with ClickHouse's documentation is that it needs improvement; I think it can be made more beginner-friendly, while the community support is really good.
Better compatibility with prior versions in terms of codebases should also be improved.
For example, it can implement some cost optimization where the license can be expensive, and compared to open-source Cassandra, cost is a concern.
I believe that DataStax Enterprise could be improved by working more on making the OpsCenter user interface more user-friendly, particularly regarding the fonts and overall UI.
My experience with pricing, setup cost, and licensing indicates that it is very expensive—ClickHouse is the most expensive option.
ClickHouse is open source with no hidden fees, offering cost-effective data management.
I found ClickHouse's pricing to be efficient in comparison to other services such as Redshift.
For smaller organizations working under a tight budget, it might not be very affordable compared to other alternatives.
ClickHouse has reduced our storage cost and improved our 99th percentile latency by 40%.
For cost optimization, after deploying the cluster on-premises and using S3 Express, approximately 5x cost savings were achieved on data storage.
ClickHouse positively impacted our organization by absorbing the whole logging system without hassle, storing logs for six months efficiently.
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.
I can confirm that the outcomes of using DataStax Enterprise show that our database uptime has increased drastically to around 99.9%.
DataStax Enterprise has positively impacted my organization because during research for a NoSQL database, developers are very positive about using DataStax Enterprise because of its really easy setup and the querying to the database is very efficient.
| Product | Mindshare (%) |
|---|---|
| ClickHouse | 5.6% |
| DataStax Enterprise | 1.8% |
| Other | 92.6% |

| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 4 |
| Large Enterprise | 8 |
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?
What benefits should users consider?
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.
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?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.
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