#Azure data studio documentation how to
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#Azure data studio documentation mac

I use Azure Data Studio as my primary work environment for everything from SQL Server code, to Python, R, PowerShell, Apache Spark ™, and more. You can have PowerShell and CMD running, or even the Azure Command-line interface (CLI) shell in the terminal where you can run a quick command. In Azure Data Studio, you can run those right in the Azure Data Studio environment – and you can run several of them. In every operating system, you have a shell (or terminal) of some type that you often need to work with. Task ListĪs your system works, you’ll see information about what it’s doing and has done in the Task History icon on the left. Pair that with github integration, and it’s where I spend most of my time. Use the File | Save Workspace As menu item to create a Workspace. This feature alone sells me on using this for day-to-day work. You can include a lot of files located in many places in a single file, such as de-workspace, that you can simply double-click to open it all at once in Azure Data Studio. The key is that Workspaces aren’t as rigid as a solution or project. Azure Data Studio also has the concept of W orkspaces, which is similar to how you might think about a solution or project in SSMS or Visual Studio. The top left two icons will handle that for you. You can connect to servers and open a directory easily from inside the tool. If you’re sold on trying out Azure Data Studio, get it installed, and get started setting up. You can also create widgets to show information about your system.

#Azure data studio documentation how to

At the end of this post, I’ll show you how to install an extension along with a few of my favorites I always use in my day-to-day coding. And here’s a cool tip: You can use almost all of them in Azure Data Studio.

#Azure data studio documentation code

I use it for everything, and Visual Studio Code has LOTS of extensions. If there isn’t something for a platform you regularly work with, contact that vendor and send them the link to create extensions, and have them publish it to the github. Do you need a tool that manages SQL Server Agent? We have that. Need search tools, check scripts, reports, or Jupyter Notebooks? Check. Need something else? Write it. that Microsoft, vendors, and even you can create extensions to do what you need. This means that Azure Data Studio works more as a platform where you can add in new functionality, themes, etc. Perhaps the biggest argument for a new tool for working with data is that Azure Data Studio has a fully functional extension feature.

#Azure data studio documentation update

On each platform, when you start Azure Data Studio, it checks itself and all your extensions and gives you the option to update them, regardless of your platform. You can also run an add-on to map the keyboard to SSMS.

#Azure data studio documentation mac

I’m typing this on a Mac right now (in Azure Data Studio, no less) and it even maps the keyboard to a Mac-like paradigm. But if you run a Mac or Linux, then you need a tool that runs on those platforms, and Azure Data Studio does just that. If you live in Windows all day exclusively, then that’s fine. When I started at Microsoft in 2006, that’s the product I worked on building. SQL Server Management Studio is an amazing tool. And if you don’t find what you need, you can make more. In Azure Data Studio, you can connect to multiple data systems, not just SQL Server, like Apache Hadoop HDFS, Apache Spark ™, and others. And those still work just fine – but Azure Data Studio goes further than those tools. You may be thinking wait – don’t we already have a lot of those? Isn’t that the SQL Server Management Studio (SSMS), or “Data Dude” (SQL Server Tools for Visual Studio) or even Visual Studio Code with the add-in for SQL Server? Azure Data Studio is a new tool that you can use to work with SQL Server. This time I’ve learned about a great new tool the team has put together. I’ll still be blogging at my regular location, and from time to time I’ll chime in here on the SQL Server blog. I’ve rejoined the SQL Server team to help with the inclusion of Apache Spark ™, Kubernetes, and the Machine Learning and AI features. After that I spent some time in Microsoft Consulting Services, then over to the Machine Learning team in Microsoft Research, and then the Machine Learning and AI team.

I started on the SQL Server team, and then helped ship Microsoft Azure.

#Azure data studio documentation professional

This blog entry comes from Buck Woody, who recently rejoined the SQL Server team from the Machine Learning and AI team.įor those of you who haven’t met me or read any of my books or blog entries, it’s great to meet you! I’ve been a data professional for over 35 years, worked at a variety of places like NASA, various consulting firms, and here at Microsoft since 2006.