Merge branch 'patch-6' of https://github.com/periclesrocha/azure-docs-pr into 20250219-periclesrocha-patch-6

Author: WilliamDAssafMSFT

articles/synapse-analytics/sql/develop-tables-external-tables.md

@@ -16,15 +16,15 @@ An external table points to data located in Hadoop, Azure Storage blob, or Azure
 
 Depending on the type of the external data source, you can use two types of external tables:
 - **Hadoop external tables** that you can use to read and export data in various data formats such as CSV, Parquet, and ORC. Hadoop external tables are available in dedicated SQL pools, but they aren't available in serverless SQL pools.
-- **Native external tables** that you can use to read and export data in various data formats such as CSV and Parquet. Native external tables are available in serverless SQL pools, and they are in **public preview** in dedicated SQL pools. Writing/exporting data using CETAS and the native external tables is available only in the serverless SQL pool, but not in the dedicated SQL pools.
+- **Native external tables** that you can use to read and export data in various data formats such as CSV and Parquet. Native external tables are available in serverless SQL pools and in dedicated SQL pools. Writing/exporting data using CETAS and the native external tables is available only in the serverless SQL pool, but not in the dedicated SQL pools.
 
 The key differences between Hadoop and native external tables:
 
 | External table type | Hadoop | Native |
 | --- | --- | --- |
-| Dedicated SQL pool | Available | Only Parquet tables are available in **public preview**. |
+| Dedicated SQL pool | Available | Parquet only |
 | Serverless SQL pool | Not available | Available |
-| Supported formats | Delimited/CSV, Parquet, ORC, Hive RC, and RC | Serverless SQL pool: Delimited/CSV, Parquet, and [Delta Lake](query-delta-lake-format.md)<br/>Dedicated SQL pool: Parquet (preview) |
+| Supported formats | Delimited/CSV, Parquet, ORC, Hive RC, and RC | Serverless SQL pool: Delimited/CSV, Parquet, and [Delta Lake](query-delta-lake-format.md)<br/>Dedicated SQL pool: Parquet |
 | [Folder partition elimination](#folder-partition-elimination) | No | Partition elimination is available only in the partitioned tables created on Parquet or CSV formats that are synchronized from Apache Spark pools. You might create external tables on Parquet partitioned folders, but the partitioning columns are inaccessible and ignored, while the partition elimination won't be applied. Don't create [external tables on Delta Lake folders](create-use-external-tables.md#delta-tables-on-partitioned-folders) because they aren't supported. Use [Delta partitioned views](create-use-views.md#delta-lake-partitioned-views) if you need to query partitioned Delta Lake data. |
 | [File elimination](#file-elimination) (predicate pushdown) | No | Yes in serverless SQL pool. For the string pushdown, you need to use `Latin1_General_100_BIN2_UTF8` collation on the `VARCHAR` columns to enable pushdown. For more information on collations, see [Collation types supported for Synapse SQL](reference-collation-types.md).|
 | Custom format for location | No | Yes, using wildcards like `/year=*/month=*/day=*` for Parquet or CSV formats. Custom folder paths aren't available in Delta Lake. In the serverless SQL pool, you can also use recursive wildcards `/logs/**` to reference Parquet or CSV files in any subfolder beneath the referenced folder. |