How to run SQL Server in a Docker container


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.

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.

LogRocket Free Trial Banner

Prerequisites
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 installed with docker-compose included. 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 mssql command 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 — master, model, msdb, and 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:

$ 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.

Conclusion
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.[Source]-https://blog.logrocket.com/how-to-run-sql-server-in-a-docker-container/
Beginners & Advanced level Docker Container Training in Mumbai. Asterix Solution's 25 Hour Docker Training gives broad hands-on practicals.



Comments

Post a Comment

Popular posts from this blog

What Is Java? A Beginner’s Guide to Java and Its Evolution

What is Java used for? Before I answer the question, what is Java used for, let me brief you about why you should choose Java. Java is highly popular and has dominated this field from early 2000’s till the present 2018. Java has been used in different domains. Some of them are listed below: Banking: To deal with transaction management. Retail: Billing applications that you see in a store/restaurant are completely written in Java. Information Technology: Java is designed to solve implementation dependencies. Android: Applications are either written in Java or use Java API. Financial services: It is used in server-side applications. Stock market: To write algorithms as to which company they should invest in.   Big Data: Hadoop MapReduce framework is written using Java. Scientific and Research Community: To deal with huge amount of data. Wait! Java can do more. Let’s see how some of the technologies make use of Java as an essential core of their functionalit...
Read more

Is Data Scientist & Data Analyst are same? Learn the Differences Now!

Image
If we talk about the hottest jobs in tech right now, then only two names will pop up in your mind those are a data analyst or data scientist.  And, that’s not only we are saying even the Harvard Business Review declared “data scientist” as the“sexiest job of the 21st century .” But there is a lot of confusion between both the names even people who have some basic knowledge of data science consider both the job profiles as one.  Well, the reason behind this confusion is both of the professions deal with big data, rather defined vaguely and sometimes used interchangeably with one another. So, here we are to explain the differences between the two of them and that too in the easiest way. Let’s begin the brief introduction of both the terms, followed by skillsets each require to understand well.   Definition a. Data Analysts Data Analysts play a vital role in the Data Science domain. As a role, they play a variety of tasks associated with collectin...
Read more

Full Stack Development : All that you need to know

What is a Full Stack Development professional? A full stack development professional is the one who is having a sound technical knowledge of each and every aspect of development – front end, back end, various operating systems among other details of the technology. These people are usually termed as “developer generalists”. The significant thing to be noted here is that full stack developer should not be confused with senior developers. In nutshell, this stack of developers can create any complex application from the scratch, provided they would have understood how each technical layer should interact with the other. Why Full Stack Development? At the beginning of this post, we have mentioned about a query that had instantly popped in the mind – why would a company require full stack development professional. Here’s the answer: 1. Creation of unique code: The developer or the agency would be able to create a unique code for multiple technologies; as they could work with ...
Read more