>> Looking for a cross-platform
Oracle Schema Conversion Solution,
join us to learn about the new experience
we are building in Azure Data Studio,
this week on Data Exposed.
[MUSIC]
Hi. I'm Anna Hoffman,
and welcome to this episode of Data Exposed.
Today, I'm joined by Alexandra and Alexander,
folks from the Azure Data team working on some exciting new stuff.
Alexandra, she's a Principal Program Manager.
She has been on the show a lot recently,
so you-all are familiar with her.
But Alexander, you're new to the show,
can you give us a brief introduction about what you do?
>> I'm a Developer here at Microsoft.
I'm working on Compete Database Migrations Team
alongside with Alexandra,
and we're providing tools and services for our customers to help
them move from compute database platform like Oracle,
MySQL, and DB2 to the Microsoft SQL Platform.
Today we are going to present you
something very interesting, so stay tuned.
>> Yeah, stay tuned, we are.
We are going to be talking about some new experience
in Azure Data Studio that I've never even seen before,
It's called The Database Schema Conversion Toolkit or DSCT.
Alexandra, can you tell us a little bit about
what this is and why you-all are creating it?
>> Sure, definitely.
DSCT is the next version of
conversion tooling for compute database platforms.
It is an idea's extension that has the capability
to run both on Linux as well as Windows.
It is a cross-platform product.
On top of that, it has
a really smooth integration with Visual Studio.
Our developers were looking
into compute migrations or conversions,
can easily have source-control versioning,
and of course,
collaborate under development of the migration projects.
>> Awesome. Cool. Just to clarify before we get further into that.
When you say compute migrations,
you're talking about migrating heterogeneously,
so things like Oracle,
is that what that means?
>> Yes, that's definitely what it means,
is other database platforms as Oracle, DB2, Sybase,
MySQL, and so on,
to any of our targets in Azure SQL,
or Postgres, or any of our targets.
This is what we define by the compute database experience.
The extension itself it targets Oracle,
Oracle to Azure SQL.
Alex is going to cover the details
for those targets in the demo as well.
>> Awesome. Cool. I'm excited to learn about this,
again, I have not seen this before.
Alexander, I just want to pass it you.
Can you show us what this is,
how it works? Anything?
>> Absolutely, Anna. Lets get into this.
As Alexandra already mentioned,
the new experience will be integrated into Azure Data Studio,
which is a cross-platform database administrator helper tool
where you can go connect to your databases,
manipulate your database objects,
create new job, and stuff like that.
We wanted to really to integrate this experience into
our DBAs that we're going to be using day in and day out.
With that, what we're
demonstrating today is a set of extensions that we
built that will help customers to migrate
their compute databases like Oracle, for instance,
and that's what we're presenting today,
to our Microsoft SQL platform,
and that includes SQL Server on-premises,
or you are running Azure SQL Database,
Managed Instance, or Synapse.
All of that will be covered right from Day 1 when we release this.
Today I will demonstrate how to convert to the SQL Server,
but the same experience applies to pretty much all of our targets.
The first thing you will have to do is obviously
get Azure Data Studio Installed and running.
That's not super hard. Just go to download pages,
download and install it.
Once you're there, you will have to install our extension,
which is called Database Schema Conversion Toolkit,
and today, as I mentioned, we're presenting Oracle to MS SQL.
But keep in mind, we call it toolkit for a reason.
There will be more to countable
support different sources and different targets,
and Alexandra will cover that in
a little bit more detail at the end after the demo.
For today's demo, we're focusing on Oracle to
Microsoft SQL because this is our main target.
Once you get this extension installed,
it has some dependencies and other extensions,
but you don't have to worry about it.
It will bring in all the dependencies that are necessary,
and everything will be lined up for you,
so just install this, and you're good to go.
The next step would be to go and connect to your Oracle server.
This is, again, a new functionality that we are bringing in
here into ADS that was not there before.
As part of this experience,
you will be able to connect your Oracle databases
and navigate through your objects.
Here for instance, I have my test Oracle 11g instance.
I can go and see my schemas,
I can go and see my objects within those schemas,
and I can start converting right from here.
The target of the conversion will
be a set of scripts that of you can later
go on and deploy onto the SQL Server Database or Azure SQL DB.
But the experience will not be
complete if you will have to switch tools.
What we are doing here is we're actually
integrating with the SQL Database projects,
which are features that already exist in the Azure Data Studio.
First step you would need to do is go
and create a new database project.
For that, you navigate through
database projects and click ''Create New''.
Here it's fairly, say, for experience,
you just give it a name.
Let's call it a Data Exposed,
and you specify location where you want that to be stored.
For the sake of the demo,
we'll just go on to one of my demo folders right here,
like this, and you select a target platform.
As I mentioned, on-prem SQL Server
support SQL DB data [inaudible],
Managed Instance, and all that,
so you'll be able to choose all that.
Target platform for the sake of the demo,
we'll just go and create on-premises SQL Server.
So you create a new project.
It may ask you to Restart real quick so
it will reload the Azure Data Studio,
get the workspace ready for you,
gets a project up and running.
Once it loads up again,
you will be able to go and proceed with
the actual conversion experience,
which I'll show you here in the brief.
Here it is, ADS reloaded.
You can see we have your project now.
Let it load a little bit.
There you go. You see this is an empty project right now.
Once, again, this is your regular SQL project.
If you're familiar with our Visual Studio experience
with SQL Server data tools,
you can go and create database projects in there.
This is exactly that same thing,
just integrated into Azure Data Studio
so you can go ahead and use it
without leaving your DBA environment
right here and design your databases.
For sake of this demo,
we are going to proceed with the actual migration
of your database objects from Oracle.
We'll go and try to migrate my HR schema.
All you have to do is basically right-click and say,
I want to convert this Microsoft SQL.
You will be graded with a visa so you can
further narrow down the selection
of the objects you want to convert.
I'll just go ahead with everything.
Now you need to select your target database project,
and this is where are we going to store
the converted scripts so that
then you can go and deploy them on database of your choice.
This is a new project, you don't have to
overwrite anything, but you can do that.
The last step is a configuration settings.
We don't have a nice polish UI for that yet,
but that's coming into future and
we'll cover that later after the demo.
For now, we'll provide you with schema of
the configuration file and you can
tweak some of the conversion settings if you have to.
For the sake of the demo, I know I don't need to tweak
anything because our default is that good.
Once you're done, it will start
scripting the objects from the HR schema,
and it will start converting them and translating them into SQL.
This can take awhile depending on the size of
your schema and your network bandwidth and all that.
Luckily for us, it happened pretty fast.
Now you can go to your database projects and
see your HR schema converted right here.
We have tables, we have procedures, we have sequences.
You can go and navigate through this and keep in
mind this is already converted to SQL
that you can go and now deploy onto
your target SQL Server database or your departments table.
We have the indexes covered and everything.
As with any heterogeneous migration tool,
they're obviously sayings is that we may not
be able to automatically convert for you.
In this case is we will just produce what
we call conversion errors and conversion warnings,
which are pretty much places where you have to go
and look into and see if what we
produce automatically works for you in case of a warning or go and
do some manual work with the conversion in case of an error.
For instance, we don't support color and triggers yet.
We just produce a conversion error in here and we comment out
the original trigger statements so it's
easier for you to work on it.
Given that it's just a script file,
you can go and modify it,
translate it to whatever it will look like into SQL,
remove the message and you're good.
Next thing, since we're integrating into
Azure Data Studio and it's built on top of VS Code,
you get all the features of the proper IDE.
You get IntelliSense support,
which suggests you what keywords you can insert on certain places.
You also get navigations across your errors.
For instance, you can see where the errors are,
but you can also see all of them here in the problems window.
Once you click on it,
it will basically bring you right to where
the problem is so you can quickly fix it,
address it, and move on, and move forward.
From here now, once you polish out all errors,
look at all the warnings,
make sure everything is good.
As I mentioned previously,
this is your regular SQL Database Project.
We are not introducing anything new just for the conversions.
From here you can basically go and publish it to
the real database or you can just go and build it,
which will basically generate a DACPAC for you.
That DACPAC can later be
deployed onto pretty much any database of your choice,
depending on which target you've selected when you create
a project. Here's your DACPAC.
You can grab it and you can go and deploy.
For the sake of the demo, I'm not going to proceed with that,
but this is pretty much a wrap of
the experience that you will get in Azure Data Studio.
Now, moving forward for
the schema
conversion/heterogenius database platforms onto Microsoft SQL.
>> Awesome, cool.
This is really cool and I like
how easy it is to use and how it's building on
what already exists and what people may already
be familiar with with database projects.
That's pretty cool. I know this is
very new depending on when folks are watching this video.
Are there current things that people
should be aware of that you're either
working on or things that are
limiting when they use this new tool?
>> This is a good question.
We're releasing it in public preview right now.
We're obviously going to provide the support and we're
expecting your feedback to come through.
But given that it's a preview,
there are obviously limitations.
One of those you could already spot when I was doing the demo,
we don't support conversion of all of
the objects and the database unfortunately right now,
but that's what we're actively working on improving.
For the public preview version,
which we're going to support is
pretty much basic table definitions to these columns, indexes,
constraints including primary key, foreign keys,
unique and check constraints,
null, not null, all of that will be covered.
But more complicated objects like procedures, functions,
and triggers, and use,
those will come a little bit later and we'll
discuss a road map in a bit.
We also support conversion of sequences.
We also support conversion of synonyms and
that pretty much a wrap for public preview release.
But we do anticipate there will be
a lot of feedback and people will guide us
towards what is most interesting
scenarios for them so we can invest more
in them and get that out to market
real quick after the initial release.
>> Awesome, cool. It seems like a great step,
especially for folks that are using cross-platform.
I see that as the biggest win for this tool.
Alexandra, previously on our series,
we've talked about SSMA or SQL Server Migration Assistant.
How does this stack compared to SSMA and what are the scenarios
that a customer might use this new tool, DSCT for?
>> Definitely SSMA is still
our main migration tool for enterprise customers and for
complex migration scenarios where you would
need to look also at procedures,
function, triggers, and use.
DSCT is actually closing the gap on one of our ordinary cases,
which was cross-platform environment.
If you are running on Linux,
and usually people coming from Oracle databases do run on Linux,
and you are looking on the tool that could run on Linux,
have a look at the DSCT.
As well as, are you a developer?
If you're a developer and looking to integrate and
collaborate on your project,
on your conversion project,
you can also leverage the features that DSCT has to offer.
I think there's a lot of richness in
terms of source control and versioning that's as well there.
>> Awesome. Wonderful. One final question
as we close out this episode,
can you give us a sneak peek at what the road map is?
>> Oh, definitely. This is just the beginning.
We are just getting started.
We are trying to build an end-to-end experience
for customers looking to leave Oracle behind.
In order to do that, they'll be definitely
other components that are going to be added.
We are looking at the net extension pack that will allow you to do
assessments as well as convert
everything and basically do an end-to-end migration.
Even more, we are looking at
building other sources and
incorporate it as the targets in the migration process.
But the we can talk more about it
in a future episode of Data Exposed.
>> Awesome. Well thanks so much both for coming on the show.
This has been an exciting episode to see what's
new in this great extension in Azure Data Studio.
I just want to thank you both for coming on the show.
To our viewers, I want to thank you
for tuning in and go check out this new tool.
We'll put some guidance in the description for you to
dive deeper and get hands on this new exogenic tool.
Leave most common, let us know what you think and
we hope to see you next time on Data Exposed.
>> [MUSIC]