- Calling programs code against a programmatic interface. This frees the table owner to change the table's structure whenever it's necessary without affecting its consumers.
- Likewise the calling programs get access to the data they need without having to know the details of the table structure, such as technical keys.
- The table owner can use code to enforce complicated business rules when data is changed.
- The table owner can enforce sophisticated data access policies (especially for applications using Standard Edition without DBMS_RLS).
Table APIs used to be a popular approach to encapsulating tables. The typical Table API comprised two packages per table; one package provided methods for inserting, updating and deleting records, and the other package provided query methods. The big attraction of Table APIs was that they could be 100% generated from the data dictionary - both Oracle Designer and Steven Feuerstein's QNXO library provided TAPI generators. And they felt like good practice because, y'know, access to the tables was shielded by a PL/SQL layer.
But there are several problems with Table APIs.
The first is that they entrench row-by-agonising-row processing. Table APIs have their roots in early versions of Oracle so the DML methods only worked with a single record. Even after Oracle 8 introduced PL/SQL collection types TAPI code in the wild tended to be RBAR: there seems to something in the brain of the average programmer which predisposes them to prefer loops executing procedural code rather than set operations.
The second is that they prevent SQL joins. Individual records have to be selected from one table to provide keys for looking up records in a second table. Quite often this leads to loops within loops. So-called PL/SQL joins prevent the optimizer from choosing good access paths when handling larger amounts of data.
The third issue is that it is pretty hard to generate methods for all conceivable access paths. Consequently the generated packages had a few standard access paths (primary key, indexed columns) and provided an dynamic SQL method which accepted a free text WHERE clause. Besides opening the package to SQL injection this also broke the Law of Demeter: in order to pass a dynamic WHERE clause the calling program needed to know the structure of the underlying table, which defeats the whole objective of encapsulation.
Which leads on to the fourth, more philosophical problem with Table APIs: there is minimal abstraction. Each package is generated so it fits very closely to the structure of the Table. If the table structure changes we have to regenerate the TAPI packages: the fact that this can be done automatically is scant recompense for the tight coupling between the Table and the API.
So although Table APIs could be mistaken for good practice in actuality they provide no real benefit. The interface is 1:1 with the table structure so it has no advantage over granting privileges on the table. Combined with the impact of RBAR processing and PL/SQL joins on performance and the net effect of Table APIs is disastrous.
We cannot generate good Data Access APIs: we need to write them. This is because the APIs should be built around business functions rather than tables. The API packages granted to other users should comprise procedures for executing transactions. A Unit Of Work is likely to touch more than one table. These have to be written by domain experts who understand the data model and the business rules.