For anyone who is still searching for further answers/examples, I can confirm that the push_down_predicate option works with ODBC data sources. Here's how I read from SQL Server (in Python).

df = glueContext.read.format("jdbc")
    .option("url","jdbc:sqlserver://server-ip:port;databaseName=db;")
    .option("user","username")
    .option("password","password")
    .option("dbtable","(select t1.*, t2.name from dbo.table1 t1 join dbo.table2 t2 on t1.id = t2.id) as users")
    .option("driver","com.microsoft.sqlserver.jdbc.SQLServerDriver")
    .load()

This also works but NOT as I expected. The predicate is not pushed down to the data source.

df = glueContext.create_dynamic_frame.from_catalog(database = "db", table_name = "db_dbo_table1", push_down_predicate = "(id >= 2850700 AND statusCode = 'ACT')")

The documentation on pushDownPredicate states: The option to enable or disable predicate push-down into the JDBC data source. The default value is true, in which case Spark will push down filters to the JDBC data source as much as possible.

Yes, AWS Glue does support reading from Data Catalog tables that are backed by PostgreSQL databases. However, the error you're encountering suggests there might be an issue with how the connection is being utilized or configured. When working with PostgreSQL in AWS Glue, it's important to ensure that the connection is properly set up and that the necessary information is being passed to the Glue job. Here are a few things to check: 1. Verify that the connection type for your PostgreSQL RDS instance is correctly set to "JDBC" in the Glue connection settings. 2. Make sure the JDBC URL, username, and password are correctly configured in the connection properties. 3. Check that the VPC, subnet, and security group settings in the Glue connection match those of your RDS instance. 4. Ensure that the IAM role associated with your Glue job has the necessary permissions to access both the Glue Data Catalog and the RDS instance. 5. When creating your dynamic frame, you may need to explicitly specify the connection name. Try modifying your code to include the connection_type parameter: ```python node_name = glueContext.create_dynamic_frame.from_catalog( database="default", table_name="my_table_name", transformation_ctx="ctx_name", connection_type="postgresql" ) ``` 6. If you're using a custom JDBC driver for PostgreSQL, make sure it's properly uploaded and configured in your Glue environment. 7. Check if there are any version compatibility issues between your PostgreSQL database and the JDBC driver being used by Glue. If you've verified all these points and are still encountering issues, it may be worth testing the connection directly using the AWS Glue connection test feature or the AWSSupport-TroubleshootGlueConnection runbook in AWS Systems Manager. These tools can help identify any network, IAM, or credential issues that might be preventing the connection from working properly. Remember that AWS Glue Studio creates unified connections for PostgreSQL data sources, which may require additional steps for accessing Secrets Manager and VPC resources. Make sure you've completed any necessary additional configuration for these unified connections. If the problem persists after checking these items, you may need to contact AWS support for further assistance, as there could be an underlying issue with the Glue service or how it's interacting with your specific PostgreSQL setup. **Sources** AWS Glue connection properties - AWS Glue Troublehsoot AWS Glue connection to a JDBC data source | AWS re:Post Using custom connectors and connections with AWS Glue Studio - AWS Glue