Merge pull request #113596 from MikeRys/patch-2

Removed SQL Pool content

Author: Jak-MS

articles/synapse-analytics/metadata/database.md

@@ -6,35 +6,29 @@ author: MikeRys
 ms.service: synapse-analytics  
 ms.topic: overview
 ms.subservice: 
-ms.date: 04/15/2020
+ms.date: 05/01/2020
 ms.author: mrys 
 ms.reviewer: jrasnick
 ---
 
 # Azure Synapse Analytics shared database
 
-Azure Synapse Analytics allows the different computational workspace engines to share databases and tables between its Spark pools (preview), SQL on-demand (preview) engine, and SQL pools.
+Azure Synapse Analytics allows the different computational workspace engines to share databases and tables between its Spark pools (preview) and SQL on-demand (preview) engine.
 
 [!INCLUDE [synapse-analytics-preview-terms](../../../includes/synapse-analytics-preview-terms.md)]
 
 A database created with a Spark job will become visible with that same name to all current and future Spark pools (preview) in the workspace as well as the SQL on-demand engine.
 
-If there are SQL pools in the workspace that have metadata synchronization enabled, or if you create a new SQL pool with the metadata synchronization enabled, these Spark created databases are automatically mapped into special schemas in the SQL pool database. 
+The Spark default database, called `default`, will also be visible in the SQL on-demand context as a database called `default`.
 
-Each schema is named after the Spark database name with an additional `$` prefix. Both the external and managed tables in the Spark-generated database are exposed as external tables in the corresponding special schema.
-
-The Spark default database, called `default`, will also be visible in the SQL on-demand context as a database called `default`, and in any of the SQL pool databases with metadata synchronization turned on as the schema `$default`.
-
-Since the databases are synchronized to SQL on-demand and the SQL pools asynchronously, there will be a delay until they appear.
+Since the databases are synchronized to SQL on-demand asynchronously, there will be a delay until they appear.
 
 ## Manage a Spark created database
 
 Use Spark to manage Spark created databases. For example, delete it through a Spark pool job, and create tables in it from Spark.
 
 If you create objects in a Spark created database using SQL on-demand, or try to drop the database, the operation will succeed. But, the original Spark database won't be changed.
 
-If you try to drop the synchronized schema in a SQL pool, or try to create a table in it, Azure returns an error.
-
 ## Handling of name conflicts
 
 If the name of a Spark database conflicts with the name of an existing SQL on-demand database, a suffix is appended in SQL on-demand to the Spark database. The suffix in SQL on-demand is `_<workspace name>-ondemand-DefaultSparkConnector`.
@@ -46,7 +40,7 @@ For example, if a Spark database called `mydb` gets created in the Azure Synapse
 
 ## Security model
 
-The Spark databases and tables, along with their synchronized representations in the SQL engines will be secured at the underlying storage level.
+The Spark databases and tables, along with their synchronized representations in the SQL engine will be secured at the underlying storage level.
 
 The security principal who creates a database is considered the owner of that database, and has all the rights to the database and its objects.
 
@@ -74,22 +68,7 @@ SELECT * FROM sys.databases;
 
 Verify that `mytestdb` is included in the results.
 
-### Exposing a Spark database in a SQL pool
-
-With the database created in the previous example, now create a SQL pool in your workspace named `mysqlpool` that enables metadata synchronization.
-
-Run the following statement against the `mysqlpool` SQL pool:
-
-```sql
-SELECT * FROM sys.schema;
-```
-
-Verify the schema for the newly created database in the results.
-
 ## Next steps
 
 - [Learn more about Azure Synapse Analytics' shared metadata](overview.md)
 - [Learn more about Azure Synapse Analytics' shared metadata Tables](table.md)
-
-<!-- - [Learn more about the Synchronization with SQL on-demand](overview.md)
-- [Learn more about the Synchronization with SQL pools](overview.md)-->