Hi, everyone, and welcome back.
Now, in today's video, we are going to discuss about the schema conversion.
Now, when we discuss about the data migration, note that it is not just about taking the backup of
the source database and loading it to the target database.
This is a very simplistic approach.
However, in real world scenarios, many times you'll come across use cases where the overall schema
also needs to be changed.
For example, the source database is based on Oracle and you want to move it to the destination database
based on PostgreSQL.
So in such type of use cases where the overall schema is also changed, the additional challenges are
introduced here.
And in order to overcome this, you can make use of the schema conversion tool also referred to as the
ACT to convert the existing database schema from one database engine to another.
For example, you see that the source database engine is a SQL Server and the destination database engine
is my SQL.
So this is where the dataset comes into picture.
Now when we discuss about the source database engine as well as the destination database engine, note
that not every type of engines are supported as part of this overall schema conversion.
So for example, when we discuss about the supported OLTP conversion you have, so if you'll see in
case if you are using the Microsoft SQL Server, you can choose the target database to be the Aurora,
Ms. SQL, the Postgres SQL, the Maria DB and various others.
And similarly for my SQL, also you can convert it to the Postgres SQL as well using the seed.
Now when we discuss about the overall schema conversion tools that are available, there are two primary
solutions that AWP offers.
The first one is the DMS schema conversion.
So this is a fully managed experience.
And second primary one that is extensively used is the schema conversion tool, which is the software.
So before we proceed further, let's go ahead and quickly look into it.
Now, if you look into the DMS dashboard, there are specific options under the convert.
For example, if you explore the migration project, it states that you can use the migration project
to convert the schema from an Oracle or SQL Server source to a MySQL or a Postgres SQL Target database.
So this is where this can be used.
So all of these are part of the DMS schema conversion.
Then you have the schema conversion, which is the software.
Now from the name itself, we can identify that this is some kind of a software that we have to install
as part of our workstation and that is exactly what it is.
So you can go ahead and download the CD for Windows, for Fedora, for Ubuntu.
So all of these download links are available.
Now.
The overall size of the installer is also quite big, so if you will quickly look into the size here
it is almost one gbps.
Now if you open up the schema conversion tool after you have installed, this is how it really looks
like.
So you have to specify the source engine.
So you have various set of engineer, Oracle, Postgres SQL, etc. So let's say that you have a microsoft
SQL Server here and then there are certain set of options whether you want to switch the engines, whether
you want to keep the engine same, but optimized for cloud and so on.
So let's say I want to switch the engine.
Then you have to specify the credentials to connect to the SQL Server.
So all of this and then you have to choose the schema and run the database migration assessment.
All right.
So I hope with this at a very high level overview, you understood both of these options.
So certain important points to note, the DMS schema conversion tool is a web version of the software
that we were discussing.
However, this specific web version provides more limited functionality compared to the desktop application.
So that desktop application has a lot of functionalities which you will not see as part of the DMS schema
conversion.
Now when we look into the primary use cases, the DMS traditionally moves smaller relational workloads,
which are less than ten DB, whereas the ICT is primarily used to migrate the large data warehouse workloads.
Apart from that, the DMS supports ongoing replication to keep the data in sync with the source.
However, a WCT does not.
And one more benefit from the site is that you can use it to run it in the offline mode.
Now, before we conclude, one thing I wanted to show you is that if you look into the FAQs associated
with the schema conversion tool, they have basically given the primary differences at the asset level
and the DMS schema level.
Now if you'll see the asset is more feature rich and it supports a lot of functionality which is not
really present as part of the DMS schema conversion tool.
Apart from that, one of the major benefit here is that the asset supports the data.
So you have the Amazon Redshift, which is supported as part of the target database.
For example, you can move from Teradata to Redshift, from IBM to Redshift, from Oracle Data Warehouse
to Redshift and so on.
So this is where also the first pointer comes into picture, where A it's is primarily used to migrate
the large data warehouse related workloads.
All right.
So that's the very high level overview about these schema conversion tools.
And with this will conclude today's video.