20260318 edit pass

Author: WilliamDAssafMSFT

azure-sql/database/elastic-query-horizontal-partitioning-migration.md

@@ -4,19 +4,21 @@ description: Learn about migration options for elastic query with EXTERNAL DATA
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: bgavrilovic
-ms.date: 03/17/2026
+ms.date: 03/18/2026
 ms.service: azure-sql-database
 ms.subservice: scale-out
 ms.topic: conceptual
 ---
 
-# Migration guide from elastic query shard map manager mode
+# Migration from elastic query shard map manager mode
 
 [!INCLUDE[appliesto-sqldb](../includes/appliesto-sqldb.md)]
 
 Elastic query in shard map manager mode (horizontal partitioning), using `EXTERNAL DATA SOURCE` type `SHARD_MAP_MANAGER`, is reaching end of support on March 31, 2027. After this date, existing workloads will continue to function but will no longer receive support, and creation of new external data sources of type `SHARD_MAP_MANAGER` will no longer be possible. This article contains options to migration from elastic query shared map manager mode.
 
-For customers using elastic query with `EXTERNAL DATA SOURCE` type `SHARD_MAP_MANAGER`, the best alternative depends on the use case for using elastic query and on the overall scenario and architecture. This article describes possible alternatives and key considerations for each.
+For customers using elastic query with `EXTERNAL DATA SOURCE` type `SHARD_MAP_MANAGER`, the best alternative depends on the use case for using elastic query and on the overall scenario and architecture. 
+
+This article describes possible alternatives to elastic query shard map manager mode, and key considerations for each.
 
 ## Microsoft Fabric
 

azure-sql/database/elastic-query-horizontal-partitioning.md

@@ -1,6 +1,6 @@
 ---
 title: Reporting Across Scaled-Out Cloud Databases
-description: how to set up elastic queries over horizontal partitions
+description: How to set up elastic queries over horizontal partitions.
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: bgavrilovic, mathoma
@@ -17,8 +17,6 @@ monikerRange: "=azuresql || =azuresql-db"
 
 [!INCLUDE [elastic-query-shard-map-manager-mode-end-of-support](includes/elastic-query-shard-map-manager-mode-end-of-support.md)]
 
-![Query across shards][1]
-
 Sharded databases distribute rows across a scaled out data tier. The schema is identical on all participating databases, also known as horizontal partitioning. Using an elastic query, you can create reports that span all databases in a sharded database.
 
 :::image type="content" source="media/elastic-query-horizontal-partitioning/horizontal-partitioning.png" alt-text="Diagram of how queries work across shards." lightbox="media/elastic-query-horizontal-partitioning/horizontal-partitioning.png":::

azure-sql/database/elastic-query-overview.md

@@ -16,7 +16,7 @@ ms.custom:
 
 [!INCLUDE [appliesto-sqldb](../includes/appliesto-sqldb.md)]
 
-The elastic query feature (in preview) enables you to run a Transact-SQL (T-SQL) query that spans multiple databases in Azure SQL Database. It allows you to perform cross-database queries to access remote tables, and to connect Microsoft and third-party tools (Excel, Power BI, Tableau, etc.) to query across data tiers with multiple databases. Using this feature, you can scale out queries to large data tiers and visualize the results in business intelligence (BI) reports.
+The elastic query feature (in preview) enables you to run a Transact-SQL (T-SQL) query that spans multiple databases in Azure SQL Database. It allows you to perform cross-database queries to access remote tables, and to connect Microsoft and non-Microsoft tools (Excel, Power BI, Tableau, etc.) to query across data tiers with multiple databases. Using this feature, you can scale out queries to large data tiers and visualize the results in business intelligence (BI) reports.
 
 ## Why use elastic queries
 

azure-sql/database/elastic-scale-glossary.md

@@ -36,13 +36,13 @@ These terms are used in [Adding a shard using Elastic Database tools](elastic-sc
 
 **Multi-shard query**: The ability to issue a query against multiple shards; results sets are returned using `UNION ALL` semantics (also known as "fan-out query"). Compare to **data dependent routing**.
 
-**Multi-tenant** and **Single-tenant**: This shows a single-tenant database and a multi-tenant database:
+**multitenant** and **Single-tenant**: This shows a single-tenant database and a multitenant database:
 
-:::image type="content" source="media/elastic-scale-glossary/multi-single-simple.png" alt-text="Diagram that shows a single-tenant database and a multi-tenant database.":::
+:::image type="content" source="media/elastic-scale-glossary/multi-single-simple.png" alt-text="Diagram that shows a single-tenant database and a multitenant database.":::
 
-Here is a representation of **sharded** single and multi-tenant databases. 
+Here is a representation of **sharded** single and multitenant databases. 
 
-:::image type="content" source="media/elastic-scale-glossary/shards-single-multi.png" alt-text="Diagram of Single and multi-tenant databases.":::
+:::image type="content" source="media/elastic-scale-glossary/shards-single-multi.png" alt-text="Diagram of Single and multitenant databases.":::
 
 **Range shard map**: A shard map in which the shard distribution strategy is based on multiple ranges of contiguous values. 
 

azure-sql/database/elastic-scale-working-with-dapper.md

@@ -61,7 +61,7 @@ The following section provides guidance for these requirements for applications
 
 ### Data-dependent routing with Dapper
 
-With Dapper, the application is typically responsible for creating and opening the connections to the underlying database. Given a type `T` by the application, Dapper returns query results as .NET collections of type `T`. Dapper performs the mapping from the T-SQL result rows to the objects of type `T`. Similarly, Dapper maps .NET objects into SQL values or parameters for data manipulation language (DML) statements. Dapper offers this functionality via extension methods on the regular [SqlConnection](/dotnet/api/system.data.sqlclient.sqlconnection) object from the ADO .NET SQL Client libraries. The SQL connection returned by the Elastic Scale APIs for DDR are also regular [SqlConnection](/dotnet/api/system.data.sqlclient.sqlconnection) objects. This allows us to directly use Dapper extensions over the type returned by the client library's DDR API, as it is also a simple SQL Client connection.
+With Dapper, the application is typically responsible for creating and opening the connections to the underlying database. Given a type `T` by the application, Dapper returns query results as .NET collections of type `T`. Dapper performs the mapping from the T-SQL result rows to the objects of type `T`. Similarly, Dapper maps .NET objects into SQL values or parameters for data manipulation language (DML) statements. Dapper offers this functionality via extension methods on the regular [SqlConnection](/dotnet/api/system.data.sqlclient.sqlconnection) object from the ADO .NET SQL Client libraries. The SQL connections returned by the Elastic Scale APIs for DDR are also regular [SqlConnection](/dotnet/api/system.data.sqlclient.sqlconnection) objects. This allows us to directly use Dapper extensions over the type returned by the client library's DDR API, as it is also a simple SQL Client connection.
 
 These observations make it straightforward to use connections brokered by the elastic database client library for Dapper.
 

azure-sql/toc.yml

@@ -845,6 +845,8 @@
         href: database/change-data-capture-overview.md
     - name: Database sharding
       items:
+      - name: Elastic Query alternatives
+        href: database/elastic-query-horizontal-partitioning-migration.md
       - name: Upgrade client library
         href: database/elastic-scale-upgrade-client-library.md
       - name: Create sharded app

docs/t-sql/statements/create-external-data-source-transact-sql.md

@@ -700,7 +700,7 @@ The `key_value_pair` is the keyword and the value for a specific connection opti
 
 Possible key value pairs are specific to the provider for the external data source vendor. For more information for each provider, see [CREATE EXTERNAL DATA SOURCE (Transact-SQL) CONNECTION_OPTIONS](create-external-data-source-connection-options.md).
 
-[!INCLUDE [sssql19-md](../../includes/sssql19-md.md)] Cumulative Update 19 and later versions introduces additional keywords to support Oracle TNS files:
+[!INCLUDE [sssql19-md](../../includes/sssql19-md.md)] Cumulative Update 19 and later versions introduce additional keywords to support Oracle TNS files:
 
 - The keyword `TNSNamesFile` specifies the filepath to the `tnsnames.ora` file located on the Oracle server.
 - The keyword `ServerName` specifies the alias used inside the `tnsnames.ora` that will be used to replace the host name and the port.
@@ -2278,7 +2278,7 @@ WITH IDENTITY = '<username>',
      SECRET = '<password>';
 ```
 
-The target server name is `WINSQL2022`, port `58137`, and it's a default instance. By specifying `Encrypt=Strict`, the connection uses TDS 8.0, and the server certificate is always verified. in this example, the `HostnameinCertificate` used is `WINSQL2022`:
+The target server name is `WINSQL2022`, port `58137`, and it's a default instance. By specifying `Encrypt=Strict`, the connection uses TDS 8.0, and the server certificate is always verified. In this example, the `HostnameinCertificate` used is `WINSQL2022`:
 
 ```sql
 CREATE EXTERNAL DATA SOURCE SQLServerInstance2
@@ -3578,7 +3578,7 @@ This example involves connecting an external data source named `MyLakeHouse` to
 
 To create a Fabric Lakehouse data source, you need to provide workspace ID, tenant, and lakehouse ID. To find the ABFSS file location of a lakehouse, go to the Fabric portal. Navigate to your Lakehouse, navigate to the desired folder location, select `...`, **Properties**. Copy the **ABFS path**, which looks something like this: `abfss://<WorkSpaceID>@<Tenant>.dfs.fabric.microsoft.com/<LakehouseID>/Files/Contoso`.
 
-Because Fabric SQL database only supports Entra ID Passthrough authentication, no database scoped credential needs to be provided, the connection will always use the user's login credentials to access the location.  
+Because Fabric SQL database only supports Microsoft Entra ID Passthrough authentication, no database scoped credential needs to be provided, the connection will always use the user's login credentials to access the location.  
 
 ```sql
 CREATE EXTERNAL DATA SOURCE MyLakeHouse