ElasticSearch DoubleCloud Transfer connector
We’ve noticed a consistent interest in optimizing ElasticSearch usage, particularly for analytical scenarios that involve calculating statistics based on data in ElasticSearch, as well as filtering and groupings. While ElasticSearch excels in search and full-text scenarios, it tends to lag behind Clickhouse significantly in terms of cost performance.
During one of our proofs of concept with a customer, we compared performance and were able to reduce query execution time from 20 seconds to less than 1 second! You can read more about that case study here. To facilitate easy migration for our users, we’ve added an ElasticSearch connector to our DoubleCloud Transfer service. You can use it to migrate your data to Clickhouse without any coding or hassle, and it includes automatic schema creation and data type definition.
Support of Clickhouse ver 23.4 and 23.5
We have incorporated Clickhouse versions 23.4 and 23.5 into our platform. The most notable improvements, and my personal favourites in these versions, are enhanced reading speed for parquet files, support for AzureBlobStorage, and query cache for production workloads.
DoubleCloud quality of life improvements
Here are some small but important changes that may improve your experience on our platform:
We have added port 443 in addition to port 8443 in Clickhouse clusters, improving compatibility with external services and restricted environments.
Now, you can also set up and activate Clickhouse internal log tables such as text_log or opentelemetry_span_log via API or directly from the console.
We have revised the logic of how empty selectors work on dashboards to increase transparency for the end user.
We have introduced the capability to display subtotals in pivot tables. Additionally, we’ve implemented changes that can be disabled if they affect usage behaviour, all manageable from the chart settings.