Data filtering for zero-ETL integrations in Oracle Database@AWS

Oracle Database@AWS zero-ETL integrations support data filtering. You can use it to control which data your source Oracle Exadata database replicates to your target data warehouse. Instead of replicating the entire database, you can apply one or more filters to selectively include or exclude specific tables. This helps you optimize storage and query performance by ensuring that only relevant data is transferred. Filtering is limited to the database and table levels. Column- and row-level filtering aren't supported.

Oracle Database and Amazon Redshift handle object name casing differently, which affects both data filter configuration and target queries. Note the following:

• Oracle Database stores database, schema, and object names in uppercase unless explicitly quoted in the CREATE statement. For example, if you create mytable (no quotes), the Oracle data dictionary stores the table name as MYTABLE. If you quote the object name in your creation statement, the Oracle data dictionary preserves the case.

• Zero-ETL data filters are case sensitive and must match the exact case of object names as they appear in the Oracle data dictionary. For example, if the Oracle dictionary stores schema and table name REINVENT.MYTABLE, then create a filter using include: ORCL.REINVENT.MYTABLE.

• Amazon Redshift queries default to lowercase object names unless explicitly quoted. For example, a query of MYTABLE (no quotes) searches for mytable.

Be mindful of the case differences when you create the Amazon Redshift filter and query the data. The filtering considerations for Oracle Database@AWS are the same as for Amazon RDS for Oracle. For examples of how case can affect data filters in an Oracle database, see RDS for Oracle examples in the Amazon Relational Database Service User Guide.