Update README.md with Custom Tables documentation (#552)

README.md

@@ -234,7 +234,39 @@ Snowflake stores all case-insensitive object names in uppercase text. In contras
 
 ### Index Support
 
-Snowflake does not utilize indexes, so neither does Snowflake SQLAlchemy.
+Indexes are supported only for Hybrid Tables in Snowflake SQLAlchemy. For more details on limitations and use cases, refer to the [Create Index documentation](https://docs.snowflake.com/en/sql-reference/constraints-indexes.html). You can create an index using the following methods:
+
+#### Single Column Index
+
+You can create a single column index by setting the `index=True` parameter on the column or by explicitly defining an `Index` object.
+
+```python
+hybrid_test_table_1 = HybridTable(
+  "table_name",
+  metadata,
+  Column("column1", Integer, primary_key=True),
+  Column("column2", String, index=True),
+  Index("index_1", "column1", "column2")
+)
+
+metadata.create_all(engine_testaccount)
+```
+
+#### Multi-Column Index
+
+For multi-column indexes, you define the `Index` object specifying the columns that should be indexed.
+
+```python
+hybrid_test_table_1 = HybridTable(
+  "table_name",
+  metadata,
+  Column("column1", Integer, primary_key=True),
+  Column("column2", String),
+  Index("index_1", "column1", "column2")
+)
+
+metadata.create_all(engine_testaccount)
+```
 
 ### Numpy Data Type Support
 
@@ -461,6 +493,117 @@ copy_into = CopyIntoStorage(from_=users,
 connection.execute(copy_into)
 ```
 
+### Iceberg Table with Snowflake Catalog support
+
+Snowflake SQLAlchemy supports Iceberg Tables with the Snowflake Catalog, along with various related parameters. For detailed information about Iceberg Tables, refer to the Snowflake [CREATE ICEBERG](https://docs.snowflake.com/en/sql-reference/sql/create-iceberg-table-snowflake) documentation.
+
+To create an Iceberg Table using Snowflake SQLAlchemy, you can define the table using the SQLAlchemy Core syntax as follows:
+
+```python
+table = IcebergTable(
+    "myuser",
+    metadata,
+    Column("id", Integer, primary_key=True),
+    Column("name", String),
+    external_volume=external_volume_name,
+    base_location="my_iceberg_table",
+    as_query="SELECT * FROM table"
+)
+```
+
+Alternatively, you can define the table using a declarative approach:
+
+```python
+class MyUser(Base):
+    __tablename__ = "myuser"
+
+    @classmethod
+    def __table_cls__(cls, name, metadata, *arg, **kw):
+        return IcebergTable(name, metadata, *arg, **kw)
+
+    __table_args__ = {
+        "external_volume": "my_external_volume",
+        "base_location": "my_iceberg_table",
+        "as_query": "SELECT * FROM table",
+    }
+
+    id = Column(Integer, primary_key=True)
+    name = Column(String)
+```
+
+### Hybrid Table support
+
+Snowflake SQLAlchemy supports Hybrid Tables with indexes. For detailed information, refer to the Snowflake [CREATE HYBRID TABLE](https://docs.snowflake.com/en/sql-reference/sql/create-hybrid-table) documentation.
+
+To create a Hybrid Table and add an index, you can use the SQLAlchemy Core syntax as follows:
+
+```python
+table = HybridTable(
+    "myuser",
+    metadata,
+    Column("id", Integer, primary_key=True),
+    Column("name", String),
+    Index("idx_name", "name")
+)
+```
+
+Alternatively, you can define the table using the declarative approach:
+
+```python
+class MyUser(Base):
+    __tablename__ = "myuser"
+
+    @classmethod
+    def __table_cls__(cls, name, metadata, *arg, **kw):
+        return HybridTable(name, metadata, *arg, **kw)
+
+    __table_args__ = (
+        Index("idx_name", "name"),
+    )
+
+    id = Column(Integer, primary_key=True)
+    name = Column(String)
+```
+
+### Dynamic Tables support
+
+Snowflake SQLAlchemy supports Dynamic Tables. For detailed information, refer to the Snowflake [CREATE DYNAMIC TABLE](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table) documentation.
+
+To create a Dynamic Table, you can use the SQLAlchemy Core syntax as follows:
+
+```python
+dynamic_test_table_1 = DynamicTable(
+    "dynamic_MyUser",
+    metadata,
+    Column("id", Integer),
+    Column("name", String),
+    target_lag=(1, TimeUnit.HOURS),  # Additionally, you can use SnowflakeKeyword.DOWNSTREAM
+    warehouse='test_wh',
+    refresh_mode=SnowflakeKeyword.FULL,
+    as_query="SELECT id, name from MyUser;"
+)
+```
+
+Alternatively, you can define a table without columns using the SQLAlchemy `select()` construct:
+
+```python
+dynamic_test_table_1 = DynamicTable(
+    "dynamic_MyUser",
+    metadata,
+    target_lag=(1, TimeUnit.HOURS),
+    warehouse='test_wh',
+    refresh_mode=SnowflakeKeyword.FULL,
+    as_query=select(MyUser.id, MyUser.name)
+)
+```
+
+### Notes
+
+- Defining a primary key in a Dynamic Table is not supported, meaning declarative tables don’t support Dynamic Tables.
+- When using the `as_query` parameter with a string, you must explicitly define the columns. However, if you use the SQLAlchemy `select()` construct, you don’t need to explicitly define the columns.
+- Direct data insertion into Dynamic Tables is not supported.
+
+
 ## Support
 
 Feel free to file an issue or submit a PR here for general cases. For official support, contact Snowflake support at: