It wasn’t long ago that the idea of running, let alone developing, a .NET application or service on any platform outside of Windows was ludicrous. But with Microsoft’s new open source focus, those days feel like a distant memory.
With the ability to develop using
dotnet core, the world of cross-platform .NET has opened up. You can now develop applications or services that can run on Windows, Mac, and even Linux.
But what about database technologies?
Many .NET-focused developers tend to lean towards using Microsoft SQL Server for their relational database needs. But SQL Server, for as long as many people can remember, can only run on a Windows platform. Our cross-platform .NET development just came to a screeching halt.
Actually, that problem has been solved as well. We can use Microsoft SQL Server across multiple platforms by leveraging Docker. Let’s take a look at how we can launch a SQL Server database inside of a Docker container for our cross-platform database needs.
To truly test this out on your own, there are some prerequisites you should be set up with.
- This is a big one: cross-platform SQL Server is only available for SQL Server 2017 and above, so make sure that version is compatible with whatever your building.
- You must have
docker-composeincluded. This is usually all handled for you if you use Docker Desktop for Mac.
- In this post, I am going to use the npm library mssql to connect, update, and query the database container. You can install that locally or globally with an
npm install mssqlcommand from any terminal.
Got those all squared away? Cool, let’s learn how to launch a SQL Server database for cross-platform development.
Launching our SQL Server container
To launch our SQL Server container, we are going to first create a
docker-compose.yml file in the root of our project. Inside of that file, we are going to define a
sql-server-db resource that uses the SQL Server 2017 image that Microsoft provides.
Here is what our
docker-compose.yml file looks like:
version: "3.2" services: sql-server-db: container_name: sql-server-db image: microsoft/mssql-server-linux:2017-latest ports: - "1433:1433" environment: SA_PASSWORD: "change_this_password" ACCEPT_EULA: "Y"
To launch our database, we can run an
up command from our command line:
$ docker-compose up -d Pulling sql-server-db (microsoft/mssql-server-linux:2017-latest)... 2017-latest: Pulling from microsoft/mssql-server-linux 59ab41dd721a: Pull complete 57da90bec92c: Pull complete 06fe57530625: Pull complete 5a6315cba1ff: Pull complete 739f58768b3f: Pull complete 0b751601bca3: Pull complete bcf04a22644a: Pull complete 6b5009e4f470: Pull complete a9dca2f6722a: Pull complete Creating sql-server-db ... done
We can see in our terminal that the
sql-server-db has been successfully created. Now we can explore how we can connect to it to run some queries. Let’s start off by just connecting to our database container:
$ mssql -u sa -p change_this_password
We should now see that we are connected to our database, and
mssql is waiting for a command. Let’s go ahead and run the
.databases command to see what databases are inside our SQL Server container:
mssql> .databases name ------ master model msdb tempdb 4 row(s) returned Executed in 1 ms
We see that the standard SQL Server databases are present —
tempdb. Let’s go ahead and create our own database and a table inside of it. We can do that by creating a SQL script file called
my_db_setup.sql that we can run inside our container.
USE master; GO CREATE DATABASE SampleDB; GO CREATE TABLE dbo.MyTable ( id bigint IDENTITY(1,1) PRIMARY KEY, name varchar(500) null ) GO
Now that we have our setup script, we can run it against our database container using
$ mssql -u sa -p change_this_password mssql> .run my_db_setup.sql USE master; OK Executed in 0 ms CREATE DATABASE SampleDB; OK Executed in 0 ms CREATE TABLE dbo.MyTable ( id bigint IDENTITY(1,1) PRIMARY KEY, name varchar(500) null ) OK Executed in 0 ms
Now that we have run our script, we can list our databases and tables to see everything that just got created:
mssql> .databases name -------- master model msdb SampleDB tempdb 5 row(s) returned Executed in 1 ms mssql> .tables database schema name type -------- ------ --------------------- ---------- master dbo MSreplication_options BASE TABLE master dbo MyTable BASE TABLE master dbo spt_fallback_db BASE TABLE master dbo spt_fallback_dev BASE TABLE master dbo spt_fallback_usg BASE TABLE master dbo spt_monitor BASE TABLE master dbo spt_values VIEW 7 row(s) returned Executed in 1 ms
Just like that, we have our own database and a table configured inside of it. All of this is running as a Docker container that we can share with others and run across a variety of different platforms.
Microsoft has been moving more and more of their frameworks, tools, and languages to support cross-platform development.
dotnet core is a huge leap forward in terms of .NET/C# development because it can run on Windows, Mac, and Linux.
But .NET is merely a framework; we also need the tools that we often use in that ecosystem to support multiple platforms. That is what we demonstrated here: SQL Server 2017 can be run on any platform by leveraging container technology.
With a few lines in a Docker compose file and a simple npm library like
mssql, we can launch a SQL Server Database on any platform. This is incredibly handy not only for production deployments but for development environments as well.
Other developers within a team can now use the same database by running
docker-compose up and running whatever seed database script we have on hand. We could even create our own Docker image that has the entire database configured and then use that image in our Docker compose file.
With things like Docker and
dotnet core, the world of cross-platform development using the .NET ecosystem is more possible than ever before.
If you have any questions about this blog post, AWS, serverless, or coding in general, feel free to ping me via twitter @kylegalbraith. Also check out my weekly Learn by Doing newsletter or my Learn AWS By Using It course to learn even more about the cloud, coding, and DevOps.
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