Style: convert formal language to informal contractions in documentation

docs/_snippets/_S3_authentication_and_bucket.md

@@ -81,7 +81,7 @@ Save the keys somewhere else; this is the only time that the secret access key w
 The bucket name must be unique across AWS, not just the organization, or it will emit an error.
 :::
 
-3. Leave `Block all Public Access` enabled; public access is not needed.
+3. Leave `Block all Public Access` enabled; public access isn't needed.
 
 <Image size="md" img={s3_a} alt="Configuring the S3 bucket settings with public access blocked" border force/>
 

docs/_snippets/_add_remote_ip_access_list_detail.md

@@ -5,7 +5,7 @@ import ip_allow_list_add_current_ip from '@site/static/images/_snippets/ip-allow
 <details>
     <summary>Manage your IP Access List</summary>
 
-From your ClickHouse Cloud services list choose the service that you will work with and switch to **Settings**.  If the IP Access List does not contain the IP Address or range of the remote system that needs to connect to your ClickHouse Cloud service, then you can resolve the problem with **Add IPs**:
+From your ClickHouse Cloud services list choose the service that you will work with and switch to **Settings**.  If the IP Access List doesn't contain the IP Address or range of the remote system that needs to connect to your ClickHouse Cloud service, then you can resolve the problem with **Add IPs**:
 
 <Image size="md" img={ip_allow_list_check_list} alt="Check to see if the service allows traffic from your IP address in the IP Access List" border />
 

docs/_snippets/_clickhouse_mysql_cloud_setup.mdx

@@ -51,7 +51,7 @@ ClickHouse Cloud automatically creates a `mysql4<subdomain>` user that shares th
 The `<subdomain>` portion corresponds to the first part of your ClickHouse Cloud hostname.
 
 This username format is required for compatibility with tools that establish secure connections but don't include [SNI (Server Name Indication)](https://www.cloudflare.com/learning/ssl/what-is-sni) data in their TLS handshake.
-Without SNI information, the system cannot perform proper internal routing, so the subdomain hint embedded in the username provides the necessary routing information.
+Without SNI information, the system can't perform proper internal routing, so the subdomain hint embedded in the username provides the necessary routing information.
 The MySQL console client is an example of a tool that requires this.
 
 :::tip

docs/_snippets/_direct_observability_integration_options.md

@@ -11,7 +11,7 @@ For plugin installation and configuration details, see the ClickHouse [data sour
 
 Datadog offers a Clickhouse Monitoring plugin for its agent which queries system tables directly. This integration provides comprehensive database monitoring with cluster awareness through clusterAllReplicas functionality. 
 :::note
-This integration is not recommended for ClickHouse Cloud deployments due to incompatibility with cost-optimizing idle behavior and operational limitations of the cloud proxy layer.
+This integration isn't recommended for ClickHouse Cloud deployments due to incompatibility with cost-optimizing idle behavior and operational limitations of the cloud proxy layer.
 :::
 
 ### Using system tables directly {#system-tables}

docs/_snippets/_gather_your_details_http.mdx

@@ -19,4 +19,4 @@ Choose **HTTPS**. Connection details are displayed in an example `curl` command.
 
 <Image img={connection_details_https} size="md" alt="ClickHouse Cloud HTTPS connection details" border/>
 
-If you are using self-managed ClickHouse, the connection details are set by your ClickHouse administrator.
+If you're using self-managed ClickHouse, the connection details are set by your ClickHouse administrator.

docs/_snippets/_gather_your_details_native.md

@@ -19,4 +19,4 @@ Choose **Native**, and the details are available in an example `clickhouse-clien
 
 <Image img={connection_details_native} size="md" alt="ClickHouse Cloud Native TCP connection details" border/>
 
-If you are using self-managed ClickHouse, the connection details are set by your ClickHouse administrator.
+If you're using self-managed ClickHouse, the connection details are set by your ClickHouse administrator.

docs/_snippets/_replication-sharding-terminology.md

@@ -3,7 +3,7 @@
 A copy of data.  ClickHouse always has at least one copy of your data, and so the minimum number of **replicas** is one.  This is an important detail, you may not be used to counting the original copy of your data as a replica, but that is the term used in ClickHouse code and documentation.  Adding a second replica of your data provides fault tolerance. 
 
 ### Shard {#shard}
-A subset of data.  ClickHouse always has at least one shard for your data, so if you do not split the data across multiple servers, your data will be stored in one shard.  Sharding data across multiple servers can be used to divide the load if you exceed the capacity of a single server. The destination server is determined by the **sharding key**, and is defined when you create the distributed table. The sharding key can be random or as an output of a [hash function](/sql-reference/functions/hash-functions).  The deployment examples involving sharding will use `rand()` as the sharding key, and will provide further information on when and how to choose a different sharding key.
+A subset of data.  ClickHouse always has at least one shard for your data, so if you don't split the data across multiple servers, your data will be stored in one shard.  Sharding data across multiple servers can be used to divide the load if you exceed the capacity of a single server. The destination server is determined by the **sharding key**, and is defined when you create the distributed table. The sharding key can be random or as an output of a [hash function](/sql-reference/functions/hash-functions).  The deployment examples involving sharding will use `rand()` as the sharding key, and will provide further information on when and how to choose a different sharding key.
 
 ### Distributed coordination {#distributed-coordination}
 ClickHouse Keeper provides the coordination system for data replication and distributed DDL queries execution. ClickHouse Keeper is compatible with Apache ZooKeeper.

docs/_snippets/_self_managed_only_automated.md

@@ -3,5 +3,5 @@ import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge';
 <CloudNotSupportedBadge/>
 
 :::note
-This page is not applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The procedure documented here is automated in ClickHouse Cloud services.
+This page isn't applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The procedure documented here is automated in ClickHouse Cloud services.
 :::

docs/_snippets/_self_managed_only_no_roadmap.md

@@ -4,6 +4,6 @@ import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge';
 <CloudNotSupportedBadge/>
 
 :::note
-This page is not applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The feature documented here is not available in ClickHouse Cloud services.
+This page isn't applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The feature documented here isn't available in ClickHouse Cloud services.
 See the ClickHouse [Cloud Compatibility](/whats-new/cloud-compatibility) guide for more information.
 :::

docs/_snippets/_self_managed_only_not_applicable.md

@@ -3,5 +3,5 @@ import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge';
 <CloudNotSupportedBadge/>
 
 :::note
-This page is not applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The procedure documented here is only necessary in self-managed ClickHouse deployments.
+This page isn't applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The procedure documented here is only necessary in self-managed ClickHouse deployments.
 :::

docs/_snippets/_self_managed_only_roadmap.md

@@ -3,6 +3,6 @@ import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge';
 <CloudNotSupportedBadge/>
 
 :::note
-This page is not applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The feature documented here is not yet available in ClickHouse Cloud services.
+This page isn't applicable to [ClickHouse Cloud](https://clickhouse.com/cloud). The feature documented here isn't yet available in ClickHouse Cloud services.
 See the ClickHouse [Cloud Compatibility](/whats-new/cloud-compatibility#roadmap) guide for more information.
 :::

docs/_snippets/clickpipes/object-storage/amazon-s3/_1-data-source.md

@@ -6,5 +6,5 @@ import Image from '@theme/IdealImage';
     <Image img={cp_step1} alt="Select imports" size="lg" border/>
 
     :::tip
-    Due to differences in URL formats and API implementations across object storage service providers, not all S3-compatible services are supported out-of-the-box. If you're running into issues with a service that is not listed under [supported data sources](/integrations/clickpipes/object-storage/s3/overview#supported-data-sources), please [reach out to our team](https://clickhouse.com/company/contact?loc=clickpipes).
+    Due to differences in URL formats and API implementations across object storage service providers, not all S3-compatible services are supported out-of-the-box. If you're running into issues with a service that isn't listed under [supported data sources](/integrations/clickpipes/object-storage/s3/overview#supported-data-sources), please [reach out to our team](https://clickhouse.com/company/contact?loc=clickpipes).
     :::

docs/_snippets/compatibility.mdx

@@ -1,6 +1,6 @@
 :::note Compatibility
-If you are noticing differences in behavior between your self-hosted ClickHouse deployment and your ClickHouse Cloud service,
+If you're noticing differences in behavior between your self-hosted ClickHouse deployment and your ClickHouse Cloud service,
 it may be related to the [compatibility setting](/operations/settings/settings#compatibility).
-In Cloud, compatibility is set when a service is created and does not change at the service level to ensure that clients get consistent behavior even as the service upgrades.
+In Cloud, compatibility is set when a service is created and doesn't change at the service level to ensure that clients get consistent behavior even as the service upgrades.
 If you wish to change compatibility, you may request to do so via [support](https://clickhouse.com/support/program).
 :::

docs/about-us/beta-and-experimental-features.md

@@ -11,7 +11,7 @@ Because ClickHouse is open-source, it receives many contributions not only from
 
 Due to the uncertainty of when features are classified as generally available, we delineate features into two categories: **Beta** and **Experimental**.
 
-**Beta** features are officially supported by the ClickHouse team. **Experimental** features are early prototypes driven by either the ClickHouse team or the community and are not officially supported.
+**Beta** features are officially supported by the ClickHouse team. **Experimental** features are early prototypes driven by either the ClickHouse team or the community and aren't officially supported.
 
 The sections below explicitly describe the properties of **Beta** and **Experimental** features:
 
@@ -34,14 +34,14 @@ Note: please be sure to be using a current version of the ClickHouse [compatibil
 - Can introduce breaking changes
 - Functionality may change in the feature
 - Need to be deliberately enabled
-- The ClickHouse team **does not support** experimental features
+- The ClickHouse team **doesn't support** experimental features
 - May lack important functionality and documentation
-- Cannot be enabled in the cloud
+- Can't be enabled in the cloud
 
 Please note: no additional experimental features are allowed to be enabled in ClickHouse Cloud other than those listed above as Beta.
 
 <!-- The inner content of the tags below are replaced at build time with a table generated from source
-     Please do not modify or remove the tags
+     Please don't modify or remove the tags
 -->
 
 <!--AUTOGENERATED_START-->

docs/about-us/distinctive-features.md

@@ -14,13 +14,13 @@
 
 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 of 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 can't 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.
+Some column-oriented DBMSs don't 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 allows ClickHouse to compete with and outperform more niche databases, like time-series ones.
 
@@ -46,11 +46,11 @@
 
 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.
+Correlated (dependent) subqueries aren't supported at the time of writing but might become available in the future.
 
 ## Vector computation engine {#vector-engine}
 
-Data is not only stored by columns but is processed by vectors (parts of columns), which allows achieving high CPU efficiency.
+Data isn't only stored by columns but is processed by vectors (parts of columns), which allows achieving high CPU efficiency.
 
 ## Real-time data inserts {#real-time-data-updates}
 
@@ -62,11 +62,11 @@
 
 ## Secondary indexes {#secondary-indexes}
 
-Unlike other database management systems, secondary indexes in ClickHouse do not point to specific rows or row ranges. Instead, they allow the database to know in advance that all rows in some data parts would not match the query filtering conditions and do not read them at all, thus they are called [data skipping indexes](../engines/table-engines/mergetree-family/mergetree.md#table_engine-mergetree-data_skipping-indexes).
+Unlike other database management systems, secondary indexes in ClickHouse don't point to specific rows or row ranges. Instead, they allow the database to know in advance that all rows in some data parts wouldn't match the query filtering conditions and don't read them at all, thus they're called [data skipping indexes](../engines/table-engines/mergetree-family/mergetree.md#table_engine-mergetree-data_skipping-indexes).
 
 ## Suitable for online queries {#suitable-for-online-queries}
 
-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").
+Most OLAP database management systems don't 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 moment when the user interface page is loading — in other words, *online*.
 

docs/about-us/history.md

@@ -44,17 +44,17 @@
 - The user can't make custom reports.
 - When aggregating over a large number of distinct keys, the data volume is barely reduced, so aggregation is useless.
 - For a large number of reports, there are too many aggregation variations (combinatorial explosion).
-- When aggregating keys with high cardinality (such as URLs), the volume of data is not reduced by much (less than twofold).
+- When aggregating keys with high cardinality (such as URLs), the volume of data isn't reduced by much (less than twofold).
 - For this reason, the volume of data with aggregation might grow instead of shrink.
-- Users do not view all the reports we generate for them. A large portion of those calculations are useless.
+- Users don't view all the reports we generate for them. A large portion of those calculations are useless.
 - The logical integrity of the data may be violated for various aggregations.
 
-If we do not aggregate anything and work with non-aggregated data, this might reduce the volume of calculations.
+If we don't aggregate anything and work with non-aggregated data, this might reduce the volume of calculations.
 
 However, with aggregation, a significant part of the work is taken offline and completed relatively calmly. In contrast, online calculations require calculating as fast as possible, since the user is waiting for the result.
 
 Yandex.Metrica has a specialized system for aggregating data called Metrage, which was used for the majority of reports.
 Starting in 2009, Yandex.Metrica also used a specialized OLAP database for non-aggregated data called OLAPServer, which was previously used for the report builder.
-OLAPServer worked well for non-aggregated data, but it had many restrictions that did not allow it to be used for all reports as desired. These included a lack of support for data types (numbers only), and the inability to incrementally update data in real-time (it could only be done by rewriting data daily). OLAPServer is not a DBMS, but a specialized DB.
+OLAPServer worked well for non-aggregated data, but it had many restrictions that didn't allow it to be used for all reports as desired. These included a lack of support for data types (numbers only), and the inability to incrementally update data in real-time (it could only be done by rewriting data daily). OLAPServer isn't a DBMS, but a specialized DB.
 
 The initial goal for ClickHouse was to remove the limitations of OLAPServer and solve the problem of working with non-aggregated data for all reports, but over the years, it has grown into a general-purpose database management system suitable for a wide range of analytical tasks.

docs/about-us/support.md

@@ -17,7 +17,7 @@
 You can also subscribe to our [status page](https://status.clickhouse.com) to get notified quickly about any incidents affecting our platform.
 
 :::note
-Please note that only subscription customers have a service level agreement on support incidents. If you are not currently a ClickHouse Cloud user – while we will try to answer your question, we'd encourage you to go instead to one of our community resources:
+Please note that only subscription customers have a service level agreement on support incidents. If you're not currently a ClickHouse Cloud user – while we will try to answer your question, we'd encourage you to go instead to one of our community resources:
 
 - [ClickHouse community Slack channel](https://clickhouse.com/slack)
 - [Other community options](https://github.com/ClickHouse/ClickHouse/blob/master/README.md#useful-links)