Merge branch 'main' into add-lakekeeper-catalog

Author: Blargian

docs/about-us/distinctive-features.md

@@ -13,15 +13,15 @@ keywords: ['compression', 'secondary-indexes','column-oriented']
 
 In a real column-oriented DBMS, no extra data is stored with the values. This means that constant-length values must be supported to avoid storing their length "number" next to the values. For example, a billion UInt8-type values should consume around 1 GB uncompressed, or this strongly affects the CPU use. It is essential to store data compactly (without any "garbage") even when uncompressed since the speed of decompression (CPU usage) depends mainly on the volume of uncompressed data.
 
-This is in contrast to systems that can store values of different columns separately, but that cannot effectively process analytical queries due to their optimization for other scenarios, such as HBase, Bigtable, Cassandra, and Hypertable. You would get throughput around a hundred thousand rows per second in these systems, but not hundreds of millions of rows per second.
+This is in contrast to systems that can store values of different columns separately, but that cannot effectively process analytical queries due to their optimization for other scenarios, such as HBase, Bigtable, Cassandra, and Hypertable. You would get throughput of around a hundred thousand rows per second in these systems, but not hundreds of millions of rows per second.
 
 Finally, ClickHouse is a database management system, not a single database. It allows creating tables and databases in runtime, loading data, and running queries without reconfiguring and restarting the server.
 
 ## Data compression {#data-compression}
 
 Some column-oriented DBMSs do not use data compression. However, data compression plays a key role in achieving excellent performance.
 
-In addition to efficient general-purpose compression codecs with different trade-offs between disk space and CPU consumption, ClickHouse provides [specialized codecs](/sql-reference/statements/create/table.md#specialized-codecs) for specific kinds of data, which allow ClickHouse to compete with and outperform more niche databases, like time-series ones.
+In addition to efficient general-purpose compression codecs with different trade-offs between disk space and CPU consumption, ClickHouse provides [specialized codecs](/sql-reference/statements/create/table.md#specialized-codecs) for specific kinds of data, which allows ClickHouse to compete with and outperform more niche databases, like time-series ones.
 
 ## Disk storage of data {#disk-storage-of-data}
 
@@ -41,9 +41,9 @@ In ClickHouse, data can reside on different shards. Each shard can be a group of
 
 ## SQL support {#sql-support}
 
-ClickHouse supports [SQL language](/sql-reference/) that is mostly compatible with the ANSI SQL standard.
+ClickHouse supports [a declarative query language](/sql-reference/) based on SQL that is mostly compatible with the ANSI SQL standard.
 
-Supported queries include [GROUP BY](../sql-reference/statements/select/group-by.md), [ORDER BY](../sql-reference/statements/select/order-by.md), subqueries in [FROM](../sql-reference/statements/select/from.md), [JOIN](../sql-reference/statements/select/join.md) clause, [IN](../sql-reference/operators/in.md) operator, [window functions](../sql-reference/window-functions/index.md) and scalar subqueries.
+Supported queries include [GROUP BY](../sql-reference/statements/select/group-by.md), [ORDER BY](../sql-reference/statements/select/order-by.md), subqueries in [FROM](../sql-reference/statements/select/from.md), the [JOIN](../sql-reference/statements/select/join.md) clause, the [IN](../sql-reference/operators/in.md) operator, [window functions](../sql-reference/window-functions/index.md) and scalar subqueries.
 
 Correlated (dependent) subqueries are not supported at the time of writing but might become available in the future.
 
@@ -67,7 +67,7 @@ Unlike other database management systems, secondary indexes in ClickHouse do not
 
 Most OLAP database management systems do not aim for online queries with sub-second latencies. In alternative systems, report building time of tens of seconds or even minutes is often considered acceptable. Sometimes it takes even more time, which forces systems to prepare reports offline (in advance or by responding with "come back later").
 
-In ClickHouse "low latency" means that queries can be processed without delay and without trying to prepare an answer in advance, right at the same moment as the user interface page is loading. In other words, online.
+In ClickHouse, "low latency" means that queries can be processed without delay and without trying to prepare an answer in advance, right at the moment when the user interface page is loading — in other words, *online*.
 
 ## Support for approximated calculations {#support-for-approximated-calculations}
 
@@ -79,7 +79,7 @@ ClickHouse provides various ways to trade accuracy for performance:
 
 ## Adaptive join algorithm {#adaptive-join-algorithm}
 
-ClickHouse adaptively chooses how to [JOIN](../sql-reference/statements/select/join.md) multiple tables, by preferring hash-join algorithm and falling back to the merge-join algorithm if there's more than one large table.
+ClickHouse adaptively chooses how to [JOIN](../sql-reference/statements/select/join.md) multiple tables, by preferring hash join and falling back to merge join if there's more than one large table.
 
 ## Data replication and data integrity support {#data-replication-and-data-integrity-support}
 
@@ -89,7 +89,7 @@ For more information, see the section [Data replication](../engines/table-engine
 
 ## Role-Based Access Control {#role-based-access-control}
 
-ClickHouse implements user account management using SQL queries and allows for [role-based access control configuration](/guides/sre/user-management/index.md) similar to what can be found in ANSI SQL standard and popular relational database management systems.
+ClickHouse implements user account management using SQL queries and allows for [role-based access control configuration](/guides/sre/user-management/index.md) similar to what can be found in the ANSI SQL standard and popular relational database management systems.
 
 ## Features that can be considered disadvantages {#clickhouse-features-that-can-be-considered-disadvantages}
 

docs/cloud/manage/backups/overview.md

@@ -165,7 +165,7 @@ Should you wish to drop tables greater than this threshold you can use setting `
 
 ```sql
 DROP TABLE IF EXISTS table_to_drop
-SYNC SETTINGS max_table_size_to_drop=2097152 -- increases the limit to 2TB
+SYNC SETTINGS max_table_size_to_drop=2000000000000 -- increases the limit to 2TB
 ```
 :::
 

docs/cloud/manage/billing/marketplace/azure-marketplace-payg.md

@@ -114,9 +114,9 @@ You will receive an email like the one below with details on configuring your ac
 
 <br />
 
-12. You will be redirected to the ClickHouse Cloud sign up or sign in page. You can either sign up using a new account or sign in using an existing account. Once you are signed in, a new organization will be created that is ready to be used and billed via the Azure Marketplace.
+12. You will be redirected to the ClickHouse Cloud sign up or sign in page. Once you redirect to ClickHouse Cloud, you can either login with an existing account, or register with a new account. This step is very important so we can bind your ClickHouse Cloud organization to the Azure Marketplace billing.
 
-13. You will need to answer a few questions - address and company details - before you can proceed.
+13. Note that if you are a new user, you will also need to provide some basic information about your business. See the screenshots below.
 
 <br />
 
@@ -128,7 +128,7 @@ You will receive an email like the one below with details on configuring your ac
 
 <br />
 
-14. Once you hit **Complete sign up**, you will be taken to your organization within ClickHouse Cloud where you can view the billing screen to ensure you are being billed via the Azure Marketplace and can create services.
+Once you hit **Complete sign up**, you will be taken to your organization within ClickHouse Cloud where you can view the billing screen to ensure you are being billed via the Azure Marketplace and can create services.
 
 <br />
 
@@ -144,4 +144,4 @@ You will receive an email like the one below with details on configuring your ac
 
 <br />
 
-15. If you run into any issues, please do not hesitate to contact [our support team](https://clickhouse.com/support/program).
+14. If you run into any issues, please do not hesitate to contact [our support team](https://clickhouse.com/support/program).

docs/cloud/manage/scaling.md

@@ -39,7 +39,9 @@ For Enterprise tier services scaling works as follows:
 :::note
 Scaling in ClickHouse Cloud happens in what we call "Make Before Break" (MBB) approach. This adds one or more replicas of the new size before removing the old replicas, preventing any loss of capacity during scaling operations. By eliminating the gap between removing existing replicas and adding new ones, MBB creates a more seamless and less disruptive scaling process. It is especially beneficial in scale-up scenarios, where high resource utilization triggers the need for additional capacity, since removing replicas prematurely would only exacerbate the resource constraints. As part of this approach we wait up to an hour to let any existing queries complete on the older replicas before we will remove them. This balances the need for existing queries to complete, while at the same time ensuring that older replicas do not linger around for too long.
 
-Please note that as part of this change, historical system table data will be retained for up to a maximum of 30 days as part of scaling events. In addition, any system table data older than December 19, 2024, for services on AWS or GCP and older than January 14, 2025, for services on Azure will not be retained as part of the migration to the new organization tiers.
+Please note that as part of this change: 
+1. Historical system table data will be retained for up to a maximum of 30 days as part of scaling events. In addition, any system table data older than December 19, 2024, for services on AWS or GCP and older than January 14, 2025, for services on Azure will not be retained as part of the migration to the new organization tiers.
+2. For services utilizing TDE (Transparent Data Encryption) system table data is currently not maintained after MBB operations. We are working on removing this limitation.
 :::
 
 ### Vertical auto scaling {#vertical-auto-scaling}
@@ -82,7 +84,7 @@ However, these services can be scaled vertically by contacting support.
 
 You can use ClickHouse Cloud [public APIs](https://clickhouse.com/docs/cloud/manage/api/swagger#/paths/~1v1~1organizations~1:organizationId~1services~1:serviceId~1scaling/patch) to scale your service by updating the scaling settings for the service or adjust the number of replicas from the cloud console.
 
-**Scale** and **Enterprise** tiers do support single-replica services. However, a service in these tiers that starts with multiple replicas, or scales out to multiples replicas can only be scaled back in to a minimum of `2` replicas.
+**Scale** and **Enterprise** tiers also support single-replica services. Services once scaled out, can be scaled back in to a minimum of a single replica. Note that single replica services have reduced availability and are not recommended for production usage.
 
 :::note
 Services can scale horizontally to a maximum of 20 replicas. If you need additional replicas, please contact our support team.

docs/cloud/reference/changelog.md

@@ -31,6 +31,15 @@ import dashboards from '@site/static/images/cloud/reference/may-30-dashboards.pn
 
 In addition to this ClickHouse Cloud changelog, please see the [Cloud Compatibility](/cloud/reference/cloud-compatibility.md) page.
 
+## August 22, 2025 {#august-22-2025}
+
+- **ClickHouse Connector for AWS Glue**  
+  You can now use the official [ClickHouse Connector for AWS Glue](/integrations/glue) that is available from the [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-eqvmuopqzdg7s). Utilizes AWS Glue’s Apache
+  Spark-based serverless engine for extracting, transforming and loading data integration between ClickHouse and other data sources. Get
+  started by following along with the announcement [blogpost](http://clickhouse.com/blog/clickhouse-connector-aws-glue) for how to create tables, write and read data between ClickHouse and Spark.
+- **Change to the minimum number of replicas in a service**  
+  Services which have been scaled up can now be [scaled back down](/manage/scaling) to use a single replica (previously the minimum was 2 replicas). Note: single replica services have reduced availability and are not recommended for production usage.
+
 ## August 13, 2025 {#august-13-2025}
 
 - **ClickPipes for MongoDB CDC now in Private Preview**