(upbeat music)
- [Narrator] Our customers use AWS Schema Conversion Tool
to migrate their on-premises databases to the AWS cloud.
AWS SCT automatically converts the source database schema
and code objects to a format compatible
with the target database.
After you connect to your source database
and load the source metadata into your project,
you can use AWS SCT in an offline mode.
When disconnected from your source database,
you can use AWS SCT to perform the following operations:
add mapping rules,
create database migration assessment reports,
convert database schemas and code,
edit your source and converted code,
save your source and converted code
as SQL scripts in a text file.
This video shows how to work with AWS SCT
in an offline mode.
We create a new a AWS SCT project,
add a source Oracle database, and connect to this database.
In the main view, we choose two database schemas
that we want to migrate to the AWS cloud.
In the source metadata tree,
we choose the Schemas node and load metadata
for the selected schemas.
Make sure that you select only the schemas
you need to migrate because loading metadata
for all database schemes may take hours.
Now, we save the AWS SCT project
and disconnect from the source database.
AWS SCT now works in an offline mode.
We add mapping rules,
which define a target database platform
for every source database schema.
For the Chinook schema,
we choose Amazon Aurora PostgreSQL-Compatible Edition
as a migration target.
For the LargeDB schema,
we choose Amazon Redshift as a migration target.
We switch to the main view to create
a database migration assessment report.
This assessment report provides a summary
of your schema conversion tasks and the details
for items that AWS SCT can't automatically convert.
AWS SCT uses the loaded metadata
of Chinook and LargeDB schemas,
which is stored in the project to create this report.
You can see that AWS SCT generated
the database migration assessment report
for Chinook and LargeDB schemas.
Now, we convert these two database schemas
to their respective target database platforms.
The target metadata tree now includes schemas
with converted code.
We can edit the database code,
which is stored in the project.
For example, you can see an action item
because AWS SCT can't convert the selected procedure.
It uses the SYSDATE function,
which returns the date from the database time zone
instead of your time zone.
We change the SYSDATE function to CURRENT_DATE
and convert this procedure again.
These changes apply to the code,
which is stored in the AWS SCT project.
Your source database code remains unchanged.
Now AWS SCT converts the procedure
and doesn't show an action item.
AWS SCT converted the Chinook database schema
to a format compatible with Amazon Aurora PostgreSQL.
We save the converted code to a text file.
We can review, edit, and then apply this code
to the Amazon Aurora PostgreSQL database.
This completes the overview of the AWS SCT offline mode.
Thanks for watching this video.
(upbeat music)