In the last two days we saw whats stretch database and how to identify the tables. Today we will see how to stretch your database to Azure cloud. Before we start I would like mention it again that the tables you choose for streching will migrate all the data to Azure which means we can stretch only the archieve tables so dont just blindly add all the tables. Just include only the required archieve tables. Continue reading “SQL Server 2016 – Configure Database Stretching”
Yesterday I covered what’s strecthing a database to cloud. Today I’m going to cover how to identify the tables which can stretch to Cloud. In most of the cases you knew which table we can move however if you are not sure when one then you can make use of this tool. I’m going to use one of the famous tool used in assessment before SQL Server upgrade to new version. Yes you are right, it’s SQL Server upgrade advisor!!
One of the new feature that’s going to accompany in SQL Server 2016. There is a significant improvement in the hardware sector moving into SSD, flash disk etc which increases the cost of hardware. Holding all the historical or archieve data in to this high performing disks is going to cost you more, assuming you got larger volume of data. As a DBA we don’t want to include this historical data into our backup plan to avoid the backup size. We can choose partial backup but again the tradeoff is in the recovery plan. Continue reading “SQL Server 2016 – What’s Stretch Database”
In our environment we have inhouse and SQL Azure databases. We will be refreshing the DEV environments weekly once from the production SQL Azure databases. As you know backups are taken care by Azure itself, so we can simply add the storage in our inhouse server and extract it as data tier application. Continue reading “Issues restoring SQL Azure bacpac due to QueryStoreStaleQueryThreshold”
Yesterday i covered what’s data masking and how can we implement in SQL Server 2016. Today I would like to continute the same topic in SQL Azure. Continue reading “SQL Azure – Dynamic Data Masking”