diff --git a/dlt/destinations/mssql/configuration.py b/dlt/destinations/mssql/configuration.py
index 88e9242f39..581da0f782 100644
--- a/dlt/destinations/mssql/configuration.py
+++ b/dlt/destinations/mssql/configuration.py
@@ -77,7 +77,7 @@ class MsSqlClientConfiguration(DestinationClientDwhWithStagingConfiguration):
     destination_name: Final[str] = "mssql"  # type: ignore
     credentials: MsSqlCredentials
 
-    create_indexes: bool = True
+    create_indexes: bool = False
 
     def fingerprint(self) -> str:
         """Returns a fingerprint of host part of a connection string"""
diff --git a/docs/website/docs/dlt-ecosystem/destinations/mssql.md b/docs/website/docs/dlt-ecosystem/destinations/mssql.md
index af2b4037eb..4d77b1d30e 100644
--- a/docs/website/docs/dlt-ecosystem/destinations/mssql.md
+++ b/docs/website/docs/dlt-ecosystem/destinations/mssql.md
@@ -15,6 +15,11 @@ This can't be included with `dlt`s python dependencies so you must installed it
 
 See instructions here to [install Microsoft ODBC Driver 18 for SQL Server on Windows, Mac and Linux](https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16)
 
+Following ODBC drivers are supported:
+* ODBC Driver 18 for SQL Server
+* ODBC Driver 17 for SQL Server
+[You configure driver name explicitly](#additional-destination-options) as well.
+
 ### Create a pipeline
 
 **1. Initalize a project with a pipeline that loads to MS SQL by running**
@@ -22,7 +27,7 @@ See instructions here to [install Microsoft ODBC Driver 18 for SQL Server on Win
 dlt init chess mssql
 ```
 
-**2. Install the necessary dependencies for BigQuery by running**
+**2. Install the necessary dependencies for MS SQL by running**
 ```
 pip install -r requirements.txt
 ```
@@ -45,12 +50,51 @@ port = 1433
 connect_timeout = 15
 ```
 
+You can also pass a SQLAlchemy-like database connection:
+```toml
+# keep it at the top of your toml file! before any section starts
+destination.mssql.credentials="mssql://loader:<password>@loader.database.windows.net/dlt_data?connect_timeout=15"
+```
+
+To pass credentials directly you can use `credentials` argument passed to `dlt.pipeline` or `pipeline.run` methods.
+```python
+pipeline = dlt.pipeline(pipeline_name='chess', destination='postgres', dataset_name='chess_data', credentials="mssql://loader:<password>@loader.database.windows.net/dlt_data?connect_timeout=15")
+```
+
+## Write disposition
+All write dispositions are supported
+
+If you set the [`replace` strategy](../../general-usage/full-loading.md) to `staging-optimized` the destination tables will be dropped and
+recreated with an `ALTER SCHEMA ... TRANSFER`. The operation is atomic: mssql supports DDL transactions.
+
+## Data loading
+Data is loaded via INSERT statements by default. MSSQL has a limit of 1000 rows per INSERT and this is what we use.
+
 ## Supported file formats
 * [insert-values](../file-formats/insert-format.md) is used by default
 
+## Supported column hints
+**mssql** will create unique indexes for all columns with `unique` hints. This behavior **may be disabled**
+
 ## Syncing of `dlt` state
 This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination)
 
 ## Data types
-
 MS SQL does not support JSON columns, so JSON objects are stored as strings in `nvarchar` column.
+
+## Additional destination options
+**mssql** destination **does not** creates UNIQUE indexes by default on columns with `unique` hint (ie. `_dlt_id`). To enable this behavior
+```toml
+[destination.mssql]
+create_indexes=true
+```
+
+You can explicitly set the ODBC driver name:
+```toml
+[destination.mssql.credentials]
+odbc_driver="ODBC Driver 18 for SQL Server"
+```
+
+### dbt support
+No dbt support yet
+