Full-stack Web Developer at a tech services company with 51-200 employees
Real User
Top 5
2024-07-12T11:58:32Z
Jul 12, 2024
For about six gigabytes, we took about two seconds to fetch all data at the maximum performance. Otherwise, it was really nice to have a medium CPU or database engine and resources. We don't have a really huge server; it's just traditional servers and traditional resources. ClickHouse is not a straightforward tool for anyone to use. Users need some time to switch from traditional things to study new concepts. We had just one client, Apache Superset. Apache Superset connects with just one connection but with too many requests. We had about 20 to 30 reports on the same page, and they work concurrently. The solution’s documentation is amazing. I would recommend the solution to other users. ClickHouse is the first step to the next generation of databases. When we deal with this amount of data and this performance, I think it's a respected technology. Overall, I rate the solution a nine out of ten.
Backend Software Engineer at a tech vendor with 51-200 employees
Real User
Top 20
2024-07-12T11:11:52Z
Jul 12, 2024
If you're considering using ClickHouse for the first time, my advice would depend on how much data you need to handle. For most scenarios where big data isn't involved, I don't think it's a good idea to use ClickHouse. SQL Server, MySQL, or PostgreSQL are well-documented and supported. The software you need to access these databases will be readily available. So, I don't see any reason to use ClickHouse for small to medium-scale scenarios. I don't think you'll find it any more difficult than other databases, apart from the SQL syntax, which is a bit different. The most challenging part with ClickHouse is dealing with the large amounts of data it handles without overloading your server. I don't think the database itself is difficult to use. However, I was primarily accessing data from it and don't have much experience with setting it up or feeding it data. I rate the overall solution a nine out of ten.
The tool is open-source, so you don't need to pay for the software itself. However, you need to consider hardware costs and maintenance. A small company can install it on a company computer. For larger companies, you might need to hire a team for maintenance and consider data safety and privacy issues. Integrating ClickHouse with other tools in our data stack was easy. It has native connections to many tools, such as Google and Amazon cloud solutions, and can easily connect with other databases. For beginners, the ease of use depends on your background. If you're familiar with relational databases, it's easy. If not, you might need to read the documentation or ask for support.
We do not use the real-time features much. Usually, we work with big data. We do not need to work with big data in real-time. We use CatBoost with ClickHouse. I always recommend the tool to others based on their requirements. If you have trouble with your queries and think that ClickHouse is slow, please review your queries. Overall, I rate the solution a ten out of ten.
Software Engineer at Activant Solutions Pvt Ltd, Jaipur
Real User
Top 20
2024-06-13T15:50:00Z
Jun 13, 2024
Although I haven't used AI with ClickHouse extensively, it's a great option because ClickHouse can handle large data volumes and perform queries very quickly. I would recommend ClickHouse to others, especially for real-time applications like chat, map locations, and AI tools. Compared to MySQL, ClickHouse handles large datasets and queries very quickly, making it a perfect choice. Overall, I would rate ClickHouse a ten out of ten.
Software Development Engineer II at a financial services firm with 10,001+ employees
Real User
Top 20
2024-05-21T14:46:24Z
May 21, 2024
I would tell other users to do a POC because it depends upon the business use case and the data. They can explore first. There's another open-source option called Apache Druid, which is a little better than ClickHouse. If that doesn't fit the use case, then they could go for ClickHouse. Overall, I would rate the solution a seven out of ten. 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. So, if your use case is real-time or logging or real-time dashboarding, then ClickHouse is a tool to consider. Otherwise, if it's batch processing and you can expect some latency, then you should go for other databases.
ClickHouse is the fastest and most resource efficient open-source database for real-time apps and analytics.
ClickHouse supports all the data sources you need to power your apps and use cases that require exceptional performance.
ClickHouse uses all available system resources to their full potential to process each analytical query as fast as possible.
ClickHouse runs on every environment, whether it’s on your machine or in the cloud.
For about six gigabytes, we took about two seconds to fetch all data at the maximum performance. Otherwise, it was really nice to have a medium CPU or database engine and resources. We don't have a really huge server; it's just traditional servers and traditional resources. ClickHouse is not a straightforward tool for anyone to use. Users need some time to switch from traditional things to study new concepts. We had just one client, Apache Superset. Apache Superset connects with just one connection but with too many requests. We had about 20 to 30 reports on the same page, and they work concurrently. The solution’s documentation is amazing. I would recommend the solution to other users. ClickHouse is the first step to the next generation of databases. When we deal with this amount of data and this performance, I think it's a respected technology. Overall, I rate the solution a nine out of ten.
If you're considering using ClickHouse for the first time, my advice would depend on how much data you need to handle. For most scenarios where big data isn't involved, I don't think it's a good idea to use ClickHouse. SQL Server, MySQL, or PostgreSQL are well-documented and supported. The software you need to access these databases will be readily available. So, I don't see any reason to use ClickHouse for small to medium-scale scenarios. I don't think you'll find it any more difficult than other databases, apart from the SQL syntax, which is a bit different. The most challenging part with ClickHouse is dealing with the large amounts of data it handles without overloading your server. I don't think the database itself is difficult to use. However, I was primarily accessing data from it and don't have much experience with setting it up or feeding it data. I rate the overall solution a nine out of ten.
The tool is open-source, so you don't need to pay for the software itself. However, you need to consider hardware costs and maintenance. A small company can install it on a company computer. For larger companies, you might need to hire a team for maintenance and consider data safety and privacy issues. Integrating ClickHouse with other tools in our data stack was easy. It has native connections to many tools, such as Google and Amazon cloud solutions, and can easily connect with other databases. For beginners, the ease of use depends on your background. If you're familiar with relational databases, it's easy. If not, you might need to read the documentation or ask for support.
We do not use the real-time features much. Usually, we work with big data. We do not need to work with big data in real-time. We use CatBoost with ClickHouse. I always recommend the tool to others based on their requirements. If you have trouble with your queries and think that ClickHouse is slow, please review your queries. Overall, I rate the solution a ten out of ten.
Although I haven't used AI with ClickHouse extensively, it's a great option because ClickHouse can handle large data volumes and perform queries very quickly. I would recommend ClickHouse to others, especially for real-time applications like chat, map locations, and AI tools. Compared to MySQL, ClickHouse handles large datasets and queries very quickly, making it a perfect choice. Overall, I would rate ClickHouse a ten out of ten.
I would tell other users to do a POC because it depends upon the business use case and the data. They can explore first. There's another open-source option called Apache Druid, which is a little better than ClickHouse. If that doesn't fit the use case, then they could go for ClickHouse. Overall, I would rate the solution a seven out of ten. 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. So, if your use case is real-time or logging or real-time dashboarding, then ClickHouse is a tool to consider. Otherwise, if it's batch processing and you can expect some latency, then you should go for other databases.