First Amazon Q Experience on Database Queries

With the initiation of Global Generative AI Challenge and collaboration of AWS Cloud Club Nepal, I came to know about the Amazon Q and able to share my experience with you all.

I am using MSSQL for my projects and I had used Azure and SSMS as IDE. For this particular task, firstly I downloaded the SSMS extension for Visual Studio Code and successfully connect to my database. In addition, I had also integrated Amazon Q in VS Code.

I got excited and without wasting a minute I started creating stored procedure and analyze the suggestion and recommendation of Amazon Q. I created new sql file with few parameters for the stored procedure. I am amazed that before starting my query after the parameter declaration, Q suggest to set no count, which I have been using while creating stored procedure previously.

Then I started writing queries further. Then it start suggesting me the possible queries inside the if condition, and it almost suggest the one which I needed.

Then when it comes to the joining condition of multiple tables, it’s able to suggest exact tables with the perfect matching condition between the tables.

When I just paste a single table declaration query, it able to explain the uses, declaration, insert statement and much more which is most valuable for us.

While writing case statement, when I started with the first when condition, then after it checks the table and suggest me the existing codes which will be probable used in cases and it was 100% correct.

It also perfectly works for triggers creation as well. It matched the exact necessary requirement for the second parameter.

The chat section was also so helpful and explained the exact needed concepts in a broader and much easier way.

In addition, Amazon Q also helps in performance tunning and query optimization by suggesting the available possible ways.

While concluding, it was a very new approach which was undertaken by mine and finds its very insightful and helpful for us in terms of writing codes by parallelly analyzing its working and performance. The reading of table columns in the background and suggesting in exact line seems fascinating for me and will be very helpful for the verification and syntax confirmation.

Not only for SQL, I have also tested Amazon Q for other programming languages such as python and java, on which it performed exceptional. I will definitely be using it in future and recommend by fellow mates regarding the possibilities and working of Amazon Q. It was really a adventurous ride through Amazon Q.