Now that I have your attention with a powerful title how about some context? It is quite common to get this error message when trying to connect to your Azure SQL Database which obviously resides on a “logical” SQL Server.
You may (or may not) have a requirement to setup a linked server to Azure SQL Database from a locally installed SQL Server. One reason could be to pull down some reports from an Azure SQL Database to a local file share. Whatever your reason is hopefully you will find this blog post useful because I ran into some complications on the way.
So what is the default isolation level for Azure SQL Database? I ran the following code to check it out.
I was creating some demo non-clustered indexes in one of my Azure SQL Databases and received the following warning when I executed this code:
I do not always use the Azure portal to make database changes or to check for certain information. I use it a lot of for blogging purposes but for some tasks I rather just run code via SSMS – SQL Server Management Studio.
Last year I wrote about Azure SQL Database extended events (https://blobeater.blog/2017/02/06/using-extended-events-in-azure/) and gave an example where I was capturing deadlocks via the ring buffer. Ever since then I wanted to do a follow-up post but using Azure storage as the target for my XEL files.
This is more complicated than using the ring buffer as the target and requires a couple of things:
- Azure storage account where you create a dedicated container for the files.
- SAS key.
- Database master key.
- Database scoped credential.
Creating copies of your Azure SQL Database is a common and relatively simple process. You can issue a TSQL statement on the master database such as:
CREATE DATABASE CodeDBcopy AS COPY OF CodeDB
vCore based performance levels are very new, currently in preview and not yet rolled out to all Azure regions (The preview is not available in the following regions: West Europe, France Central, UK South, and UK West.). It does offer a totally different approach to sizing your database.
I have come to understand the importance of using columnstore indexes when my queries are aggregating and scanning across many millions of rows.