My situation is similar but on top I have external systems which are not supported by VP at moment:
Hive - it has different data types supported across versions (very complex)
Huawei Data Lake Insight - Hive based, but only limited specific data types
Huawei DWS - Postgres like structure, but customized by Huawei
Here VP is not helping me with my case, if I can easily create my specific product mapping within VP with column level overrides, it will be great, but at moment I export from VP DDL which I parse (yes, I have grammar parser) and convert it into specific Vendor data types.
I think I am not the only one. If someone works with cloud storage engines like AWS, Huawei or Alibaba, Google they have their own specific data types in products. You as Visual Paradigm cannot keep up with all of Vendors. By trying to keep up, you slow down the users (me), so that is the reason why I suggest introduce fully customizable data type mappings (global, column override levels) so I can come to VP and define my own mapping. See in some cases I talk about 20 data types only (Hive Huawei clone), in some its more complex like Postgres which supports super-wide variety of data types.