This article is going to introduce you to Spring Boot with GraphQL. We’ll walk through a simple beer app to show you what it can do. So you have built this really sweet API with all the gets, puts, and deletes you can think of. Your baby is just beautiful the way it is, right? Well, maybe developer Joe thinks …
On my last two projects, I decided to give Azure Data Studio a try to see how it measured up to SSMS. Azure Data Studio gives you a more modern editor experience. It’s comparable to Visual Studio Code with IntelliSense, source control with GIT, and an integrated terminal for Powershell or SQLMD commands.
Azure Data Studio was built with a data platform user in mind, and its easy editing and export options, built-in charting of query results, and customizable dashboards make it an incredibly valuable tool.
In this post, I’ll go over some of the basics of how to use Azure Data Studio.
This is just a short article (more of a blog-ette than a full blog) about some things we as developers need to consider when sending queries to Microsoft’s SQL Server. While some of this information may also be true for other flavors of database servers, these things are known to be true for SQL Server.
This 33-minute video features Keyhole Principle Consultant Mat Warger at our internal employee lunch and learn in November 2020. He discusses GraphQL’s main features and how it’s beneficial for use in modern APIs.
GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. Basically, it provides a better way to think about your data!
Every long-term project will outlive at least some of the technologies it was originally built with. For example, a project I have been involved with recently ran into this situation. The app is hosted on Heroku, and over the years, the available MongoDB add-ons have changed and dwindled until now, there is only one.
Several migrations between MongoDB add-ons have already happened because of shutdowns. So, it was decided that rather than migrating to the last one still in existence, the project would switch to using PostgreSQL, which is supported directly by the Heroku team.