Differences Between Transparent Tables, Pooled Tables & Cluster Tables.

What Are The Differences Between Transparent Tables, Pooled Tables & Cluster Tables?

Differences between transparent, pooled and cluster tables are:

 Transparent tables have a one to one relationship with a physical table in an underlying database where as pooled tables and cluster tables have many to one relationship with a physical table in the underlying database (Relationship between tables in ABAP Dictionary & Underlying database).

 For each transparent table there will be exactly only one table in the underlying database whereas many pooled tables are stored in a single table in an underlying database called table pool. Similarly many cluster tables are stored in a single table in the database called a table cluster

 In case of transparent tables, the underlying database table will have the same name, same number of fields and the fields will also have the same names as defined in ABAP Dictionary whereas for pooled tables and cluster tables the underlying database table will have different name, different number of fields and fields will have different names from what has been defined in ABAP Dictionary.

 Transparent tables can have one or more primary key Whereas Primary key of each pooled table of a table pool need not be same whereas Primary key of each cluster table of a table cluster should have at least one key in common.

 Secondary indexes can be created for transparent tables, but for pooled and cluster tables we cannot create any secondary index.

 Transparent tables can be accessed via both Native and Open SQL whereas pooled and cluster table can be accessed by Open SQL only.

 Transparent tables are used to hold application data which includes both master data as well as transaction data. Pooled tables reduce the amount of database resources needed when many small tables have to be opened at the same time. Cluster tables are used when the tables have primary key in common and data in these tables are all accessed simultaneously.