Document new behavior flags for dbt-databricks

website/docs/reference/global-configs/databricks-changes.md

@@ -11,6 +11,8 @@ The following are the current [behavior change flags](/docs/reference/global-con
 | [`use_info_schema_for_columns`](#use-information-schema-for-columns) | 1.9.0                   | TBD                        |
 | [`use_user_folder_for_python`](#use-users-folder-for-python-model-notebooks)  | 1.9.0                   | TBD                        |
 | [`use_materialization_v2`](#use-restructured-materializations)      | 1.10.0                  | TBD                        |
+| [`use_managed_iceberg`](#use-managed-iceberg)  | 1.11.0  |  TBD                                                     |
+| [`use_replace_on_for_insert_overwrite`](#use-replace-on-for-insert_overwrite-strategy)   | 1.11.0   | TBD                    |
 
 ## Use information schema for columns
 
@@ -178,3 +180,11 @@ models:
 ```
 
 </File>
+
+## Use managed Iceberg
+
+The `use_managed_iceberg` flag is `False` by default and results in a [UniForm](https://www.databricks.com/blog/delta-uniform-universal-format-lakehouse-interoperability) table when `table_format` is set to `iceberg`. When this flag is set to `True`, the table is created as a [managed Iceberg table](https://docs.databricks.com/aws/en/tables/managed).
+
+## Use `replace on` for `insert_overwrite` strategy
+
+The `use_replace_on_for_insert_overwrite` flag is only relevant when using incremental models with the `insert_overwrite` strategy on SQL warehouses. The flag is `True` by default and results in using the [`insert into ... replace on`](https://docs.databricks.com/aws/en/sql/language-manual/sql-ref-syntax-dml-insert-into#replace-on) syntax to perform dynamic partition/cluster overwrites, which is the same behavior as in cluster computes. When the flag is set to `False`, `insert_overwrite` will truncate the entire table when used with SQL warehouses. The flag is not relevant for cluster computes because the `insert_overwrite`'s behavior has always been dynamic partition/cluster overwrites in cluster computes.

website/docs/reference/resource-configs/databricks-configs.md

@@ -240,9 +240,13 @@ insert into table analytics.databricks_incremental
 
 ### The `insert_overwrite` strategy
 
-This strategy is most effective when specified alongside a `partition_by` clause in your model config. dbt will run an [atomic `insert overwrite` statement](https://spark.apache.org/docs/3.0.0-preview/sql-ref-syntax-dml-insert-overwrite-table.html) that dynamically replaces all partitions included in your query. Be sure to re-select _all_ of the relevant data for a partition when using this incremental strategy.
+This strategy is most effective when specified alongside a `partition_by` or `liquid_clustered_by` clause in your model config. dbt will run an [atomic `insert into ... replace on` statement](https://docs.databricks.com/aws/en/sql/language-manual/sql-ref-syntax-dml-insert-into#replace-on) that dynamically replaces all partitions/clusters included in your query. Be sure to re-select _all_ of the relevant data for a partition/cluster when using this incremental strategy. 
 
-If no `partition_by` is specified, then the `insert_overwrite` strategy will atomically replace all contents of the table, overriding all existing data with only the new records. The column schema of the table remains the same, however. This can be desirable in some limited circumstances, since it minimizes downtime while the table contents are overwritten. The operation is comparable to running `truncate` and `insert` on other databases. For atomic replacement of Delta-formatted tables, use the `table` materialization (which runs `create or replace`) instead.
+When using `liquid_clustered_by`, the `replace on` keys used will be equivalent to the `liquid_clustered_by` value (same as `partition_by` behavior). 
+
+If [`use_replace_on_for_insert_overwrite`](/reference/global-configs/databricks-changes#use-replace-on-for-insert_overwrite-strategy) is set to `True` in SQL warehouses or if cluster computes are used, this strategy will run a [partitionOverwriteMode='dynamic' `insert overwrite` statement](https://docs.databricks.com/aws/en/delta/selective-overwrite#dynamic-partition-overwrites-with-partitionoverwritemode-legacyl) instead. If [`use_replace_on_for_insert_overwrite`](/reference/global-configs/databricks-changes#use-replace-on-for-insert_overwrite-strategy) is set to `False` in SQL warehouses, this strategy will truncate the entire table.
+
+If no `partition_by` or `liquid_clustered_by` is specified, then the `insert_overwrite` strategy will atomically replace all contents of the table, overriding all existing data with only the new records. The column schema of the table remains the same, however. This can be desirable in some limited circumstances, since it minimizes downtime while the table contents are overwritten. The operation is comparable to running `truncate` and `insert` on other databases. For atomic replacement of Delta-formatted tables, use the `table` materialization (which runs `create or replace`) instead.
 
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