reorganise data visualization section

Author: Blargian

docs/integrations/data-ingestion/apache-spark/spark-jdbc.md

@@ -11,8 +11,12 @@ doc_type: 'guide'
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 import TOCInline from '@theme/TOCInline';
+import ClickHouseSupportedBadge from '@theme/badges/ClickHouseSupported';
 
 # Spark JDBC
+
+<ClickHouseSupportedBadge/>
+
 JDBC is one of the most commonly used data sources in Spark.
 In this section, we will provide details on how to
 use the [ClickHouse official JDBC connector](/integrations/language-clients/java/jdbc) with Spark.

docs/integrations/data-ingestion/aws-glue/index.md

@@ -13,9 +13,12 @@ import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 import notebook_connections_config from '@site/static/images/integrations/data-ingestion/aws-glue/notebook-connections-config.png';
 import dependent_jars_path_option from '@site/static/images/integrations/data-ingestion/aws-glue/dependent_jars_path_option.png';
+import ClickHouseSupportedBadge from '@theme/badges/ClickHouseSupported';
 
 # Integrating Amazon Glue with ClickHouse and Spark
 
+<ClickHouseSupportedBadge/>
+
 [Amazon Glue](https://aws.amazon.com/glue/) is a fully managed, serverless data integration service provided by Amazon Web Services (AWS). It simplifies the process of discovering, preparing, and transforming data for analytics, machine learning, and application development.
 
 ## Installation {#installation}

docs/integrations/data-ingestion/azure-data-factory/overview.md

@@ -7,8 +7,12 @@ title: 'Bringing Azure Data into ClickHouse'
 doc_type: 'guide'
 ---
 
+import ClickHouseSupportedBadge from '@theme/badges/ClickHouseSupported';
+
 # Bringing Azure Data into ClickHouse
 
+<ClickHouseSupportedBadge/>
+
 Microsoft Azure offers a wide range of tools to store, transform, and analyze
 data. However, in many scenarios, ClickHouse can provide significantly better
 performance for low-latency querying and processing of huge datasets. In

docs/integrations/data-ingestion/azure-data-factory/using_azureblobstorage.md

@@ -8,7 +8,6 @@ doc_type: 'guide'
 ---
 
 import Image from '@theme/IdealImage';
-
 import azureDataStoreSettings                   from '@site/static/images/integrations/data-ingestion/azure-data-factory/azure-data-store-settings.png';
 import azureDataStoreAccessKeys                 from '@site/static/images/integrations/data-ingestion/azure-data-factory/azure-data-store-access-keys.png';
 

docs/integrations/data-ingestion/azure-synapse/index.md

@@ -11,9 +11,12 @@ import TOCInline from '@theme/TOCInline';
 import Image from '@theme/IdealImage';
 import sparkConfigViaNotebook from '@site/static/images/integrations/data-ingestion/azure-synapse/spark_notebook_conf.png';
 import sparkUICHSettings from '@site/static/images/integrations/data-ingestion/azure-synapse/spark_ui_ch_settings.png';
+import ClickHouseSupportedBadge from '@theme/badges/ClickHouseSupported';
 
 # Integrating Azure Synapse with ClickHouse
 
+<ClickHouseSupportedBadge/>
+
 [Azure Synapse](https://azure.microsoft.com/en-us/products/synapse-analytics) is an integrated analytics service that combines big data, data science and warehousing to enable fast, large-scale data analysis.
 Within Synapse, Spark pools provide on-demand, scalable [Apache Spark](https://spark.apache.org) clusters that let users run complex data transformations, machine learning, and integrations with external systems.
 

docs/integrations/data-visualization/community_integrations/_category_.json

@@ -0,0 +1,5 @@
+{
+  "label": "Third-party",
+  "collapsible": true,
+  "collapsed": true,
+}