A team has a website that provides the latest real estate news to subscribers. It has included a Java frontend, backend, and a MySQL database to store user information. They plan to migrate the MySQL database to PostgreSQL database to use some features that MySQL does not have. At the same time, the development lead has raised extra requirements.

Answer options:

A.DMS cannot handle the task of migration from MySQL to PostgreSQL. When database engines need to be changed, use the AWS Schema Conversion Tool to convert existing database schema, including tables, indexes, and most application code, to the target platform.
B.DMS can handle the task of migration from MySQL to PostgreSQL. It can achieve task 1 by using the Selection Rule for column “user_activity” in table “user_info”. However, it cannot do tasks 2 and 3.
C.DMS can handle the task of migration from MySQL to PostgreSQL. It can achieve task 1 by using the Selection Rule for column “user_activity” in table “user_info”. Task 2, can also be completed by using a “Transformation Rules and Actions” to remove the columns starting with “test”. However, for task 3, DMS cannot do that.
D.DMS can handle the task of migration from MySQL to PostgreSQL. And all tasks can be achieved by specifying Table Selection and Transformations using JSON.

Correct Answer – D
 
DMS can handle the task of migration from MySQL to PostgreSQL, as shown below.
The first task can be achieved by using a "Selection Rule". The below diagram depicts using a filter for the "Customers" table on the column "AgencyID" where the values are between "01" and "85"
The second task can be achieved by using the JSON template for "Transformation Rules," as shown below.
{
 "rules": [{
 "rule-type": "selection",
 "rule-id": "1",
 "rule-name": "1",
 "object-locator": {
"schema-name": "test",
"table-name": "%"
 },
 "rule-action": "include"
 }, {
 "rule-type": "transformation",
 "rule-id": "2",
 "rule-name": "2",
 "rule-action": "remove-column",
 "rule-target": "column",
 "object-locator": {
"schema-name": "test",
"table-name": "latestnews",
"column-name": "test%"
 }
 }]
 }
The third task can also be achieved by using the JSON template for "Transformation Rules" as shown below.
{
 "rules": [{
 "rule-type": "selection",
 "rule-id": "1",
 "rule-name": "1",
 "object-locator": {
"schema-name": "test",
"table-name": "%"
 },
 "rule-action": "include"
 }, {
 "rule-type": "transformation",
 "rule-id": "2",
 "rule-name": "2",
 "rule-action": "add-prefix",
 "rule-target": "table",
 "object-locator": {
"schema-name": "test",
"table-name": "%"
 },
 "value": "DMS_"
 }]
 
}
Option A is incorrect. This option says DMS cannot handle migration. Indeed migration from MySQL to PostgreSQL is supported by DMS.
Option B is incorrect. This option says tasks 2 and 3 cannot be done. In fact, tasks 2 and 3 can be achieved, as shown above.
Option C is incorrect: Because task 3 can be achieved via “Transformation Rules and Actions”. A reference is in
https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Tasks.CustomizingTasks.TableMapping.html.
Option D is CORRECT: Because DMS can perform this migration with all three tasks being achievable.