Introducing SQL Server on Linux
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Introducing SQL Server on Linux


Coming up, we’ll take a look at SQL Server on Linux. I’ll show you how you can download and install SQL Server on a Linux virtual machine. Run your SQL Server based apps
inside of Docker Containers. And improve the performance of
your applications with Columnstore, one of the many powerful features in SQL Server. In March of this year, we announced
that we are bringing SQL Server to Linux. Today we’re announcing that SQL Server
on Linux is available in public preview. The first thing I want to show you is how easy it is to download and install on Linux in under 60 seconds. Here on my Macbook, I’m running a
red hat enterprise Linux VM To kick off the installation,
I run Yum install mssql-server. While that’s installing, I’d like to tell
you a little bit more about SQL Server on Linux. The scope of the first SQL Server
release on Linux is the relational database only. Most of the key features of SQL
Server 2016 will be included, such as Transparent data encryption, Always encrypted, Row level security, In memory tables, Columnstore and more. Looks like the installation completed. So now you can see that we can install SQL
Server on Linux in under a minute. That’show easy it is to get installed on your own VM. But you can also just grab a Docker
image with SQL Server pre-installed. Let’s take a look at an example of a
Docker based application with SQL Server container. Let’s first look at the application architecture. First we have a voting application which is a python-based application that registers a user’s vote for either dogs or cats. The vote is stored in the Redis cache DB. And then a java worker app container move the vote from the Redis cache DB
to the SQL Server database. And then a node-based application displays the results to the user. Now let’s go back and Docker
compose up our application. Now that the application is up we can bring up the voting application and the results. Let’s go ahead and vote for dogs. That will register the vote in the database
and we can see the results. Now lets take a look inside of the
database and see what’s happening. To do that, I’ll run a command in the command palette to connect to a SQL Server database. I’ve already pre casched a connection
to my votes database running my SQL Server container. We can see that we are now connected
down here in the lower right hand corner and we can begin executing queries. So here we can see that
we have a vote for dogs which is B. and we can update the vote to A. And see that the vote has
now changed from dogs to cats. So you can see from this basic example that SQL Server operates just like any other SQL Server. Even when it runs inside of a Docker container. Now let me finish up by showing you one of the many powerful capabilities of SQL Server. Columnstores stores data on disk and in memory in a special order for fast access
and better compression rates. I’ll run this simple job application. And while it’s running, i’ll explain what it does. First, it connects to SQL Server. Then it drops a database if it already exists and recreate a new empty
database for us to insert data into. Then it has a simple data generation routine which inserts data into a products table and has a price column that stores the price of objects. In this case, we’re inserting five
million rows worth of data. After the data is inserted, we’ll run
a typical select sum query to sum up the price of all of the five million rows. Then we’ll create the clustered columnstore
index to improve performance. And we’ll rerun the query to see
the improvement in performance. So at this point, we’re inserting the
five million rows into the table. Now that the data has been inserted we can see that the first query took
382 milliseconds to run Now we’ll add a Clustered Columnstore index to the table to improve performance. After the Clustered Columnstore index is added, the query time is only seven milliseconds So we can see that we got
fifty times better performance just on my Macbook and with only five million rows. All I had to do was run a one-line T-SQL
query to add the index. The best part is that we just announced that all the programmability features previously available in enterprise edition are now available in all editions of SQL Server. Both on Linux and on SQL Server 2016 FP1 on Windows which we also just released today. Hopefully this gives you a quick
idea of how seamlessly SQL Server fits into Linux and Docker. It’s SQL Server as you know it today,
it’s just native to Linux. It works with your data and your favorite tools, application, frameworks and programming languages. It’s even easy to get. So go grab the public preview at the link below. We’re looking forward to hearing your feedback and answering your questions
over on Stack Overflow. Thanks for watching. Microsoft Mechanics www.microsoft.com/mechanics

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