Backend Software Engineer at a tech vendor with 51-200 employees
Real User
Top 20
2024-07-12T11:11:52Z
Jul 12, 2024
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.
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.
The clusters are not perfect. We had a lot of troubles while deploying a whole cluster. We must tune some sequences, so we must have experience with the product. I worked a lot with bare metal. However, working with the cloud is a little bit harder. When we need to start up and shut down some nodes, we need to start or shut down the whole cluster. It is not so in Databricks.
Software Engineer at Activant Solutions Pvt Ltd, Jaipur
Real User
Top 20
2024-06-13T15:50:00Z
Jun 13, 2024
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.
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.
ClickHouse has its own concept of database triggers and doesn't support traditional database triggers.
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.
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.
The clusters are not perfect. We had a lot of troubles while deploying a whole cluster. We must tune some sequences, so we must have experience with the product. I worked a lot with bare metal. However, working with the cloud is a little bit harder. When we need to start up and shut down some nodes, we need to start or shut down the whole cluster. It is not so in Databricks.
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.
Some features, like connecting to third-party applications or the cloud, could be better.