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Category: Cloud

Creating Users in Azure SQL Database

Kenneth Fisher takes us through a nuance in adding users to Azure SQL Database:

Awesome! I did say I preferred code didn’t I? I am noticing a slight problem though. I don’t actually have a login yet. So I look in object explorer and there is no instance level security tab. On top of that when I try to create a login with code I get the following error:

Msg 5001, Level 16, State 2, Line 1
User must be in the master database.

Read on for the whole process.

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Migrating SSIS to Azure Data Factory

Koen Verbeeck has some articles for us:

For quite some time now, there’s been the possibility to lift-and-shift your on-premises SSIS project to Azure Data Factory. There, they run in an Integration Runtime, a cluster of virtual machines that will execute your SSIS packages. In the beginning, you only had the option to use the project deployment model and host your SSIS catalog in either an Azure SQL DB, or in a SQL Server Managed Instance.

But over time, features were added and now the package deployment model has been supported for quite some time as well. Even more, the “legacy SSIS package store” is also supported. For those who still remember this, it’s the SSIS service where you can log into with SSMS and see which packages are stored in the service (either the file system or the MSDB database) and which are currently running.

Read on for much more detail on the topic.

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External Tables vs T-SQL Views in Synapse

James Serra explains the differences between external tables and T-SQL views in Azure Synapse Analytics when querying from Data Lake Storage:

A question that I have been hearing recently from customers using Azure Synapse Analytics (the public preview version) is what is the difference between using an external table versus a T-SQL view on a file in a data lake?

Note that a T-SQL view and an external table pointing to a file in a data lake can be created in both a SQL Provisioned pool as well as a SQL On-demand pool.

Here are the differences that I have found:

Click through for the differences.

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Date and Time Functions in Cosmos DB

Hasan Savran walks us through date and time functions in Azure Cosmos DB:

Json does not have datetime data type, you need to keep the datetime information in string. This can be a problem for database engines specially if user needs to search by date or sort by date. Cosmos DB team introduced bunch of datetime functions to the Azure Cosmos DB database engine this month. You can read my older post about DateTime in CosmosDB if you like to know how Azure CosmosDB saves the datetime in documents. I will cover the new datetime functions in this post. Here is the list of the functions 

Click through for those functions and how you can use them.

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Geospatial Analysis with Azure Data Explorer

Chris Webb continues along a theme:

Since last week’s blog post about dynamic M parameters generated so much interest, this week I thought I’d give you another example of something cool you can do with them when you’re using Azure Data Explorer (ADX) as a DirectQuery source in Power BI: geospatial analysis.

Let’s say you work for a chain of supermarkets and want to use Power BI see what other competing stores are close to one of your stores.

Read on for the rest of the story.

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SQL Server Installation Options for Testing Azure DevOps Deployments

Kevin Chant looks at the different options available when trying to set up local testing of SQL Server databases using Azure DevOps deployments:

One way you can work around the above scenario is to install multiple virtual machines. Now the first thing you might realize is that this will also take up a lot of compute and storage.

In reality, I use to use this method myself in the past using Hyper-V. To reduce the amount of storage the virtual machines used in Hyper-V I use to used parenting disks.

Since the introduction of containers and Docker this has become a less popular option. However, you can still read an old post of mine with tips in here.

Click through for additional options.

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Azure Elastic Queries, Jobs, and Transactions

Steve Hughes walks us through three Elastic concepts in Azure:

Elastic queries allow developers to interact with data from multiple databases supported on the Azure SQL database platform including Synapse. Elastic queries are often referred to as Polybase which is currently implemented in SQL Server 2019 and Azure Synapse. The key difference is that elastic queries only allow you to interact with other Azure SQL Databases but not Hadoop or other database implementations (e.g. Teradata or Oracle). Part of the confusion comes from the fact that the implementation looks very similar. Both toolsets use external tables in SQL Server to interact with the connected data sources. However, Polybase requires additional components to run whereas elastic queries are ready to go without additional setup.

Read on for more information, including demos.

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