Recently I got to a stage where I leveraged Databricks to the best of my ability to join couple of CSV files together, play around some aggregations and then output it back to a different mount point ( based on Azure Storage) as a parquet file, I decided that I actually wanted to move this data into Azure SQL DB, which you may want to do one day.
It was just a matter of time until I started combining my cloud experience with “different” flavours of SQL Server. I haven’t used Linux since my university days (Oracle – errgh) but recently some Friends of mine ( using LAMP stack ) asked me couple of questions about SQL Server Linux.
There are many quality resources regarding SQL Server 2019, from eBooks to videos about the newest features and how one would implement these within your business. I recommend the following book, not because I was co-author, more so of the fact that the other authors have brilliant chapters giving quality high level information (with enough detail) to understand SQL Server 2019.
I mean, who better than Buck Woody to talk about Big Data Clusters???!
Moving to public cloud such as Azure, AWS or even private cloud services you need to be tracking costs and seeing if you are “effective”. What is the best way of doing this with Microsoft Azure?
Unfortunately, this is not an on-premises SQL Server install because I do not have the right operating system available for SQL Server 2019, which includes the below:
So, I am going to use my clicking skills and spin a Machine up in Azure utilizing the market place, so I can get an image of SQL Server installed on the VM already.
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