Azure SQL Database

Azure SQL Database Elasticity – Queries, Jobs, and Transactions

Do you want to learn Azure SQL Database Elasticity? In this recent webinar, 3Cloud Director of Consulting, Steve Hughes, explores the flexibility of Azure SQL Database and how it makes an even better target for solutions that could only be supported on premises.

Steve dives deep into Azure SQL Database Elasticity, covering:

  • Elastic Queries (still in preview)
    • These are similar to Polybase functionality found in SQL Server 2019 and Azure Synapse but only for use with Azure SQL Database and Azure Synapse.
    • Elastic Queries strategies like vertical partitioning, horizontal partitioning or Sharding and data virtualization.
    • Touches upon cost information.
  • Elastic Jobs
    • Provides a mechanism to support T-SQL scripts to be run across one or more databases in parallel, on demand or on a schedule.
    • Elastic Jobs can be created in the portal, with PowerShell, with REST, or SQL.
    • Elastic Job target groups (i.e. databases, servers, pools, and Shard Maps).
    • Jobs and job steps.
  • Elastic Transactions
    • Allows you to create cross database transactions in Azure SQL Database.
    • What transactions it supports and its limitations.

All these elasticity topics will also be demoed in this webinar. So, if you’d like to learn more about Azure SQL Database elasticity and how to use this flexibility in your solutions, this webinar is for you. You can watch the complete webinar below.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudAzure SQL Database Elasticity – Queries, Jobs, and Transactions
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The Database World of Azure

Do you want to learn how databases in Azure are more than SQL Server? In a recent webinar, Steve Hughes, reviews Azure’s database offerings. If you go to the Microsoft Azure site and open the database bucket, you’ll see quite a few database offerings from Microsoft. This webinar will look at use cases and costs around these, as well as related functionality.

3CloudThe Database World of Azure
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Azure Storage Options

Azure Storage Options (1)

We all know life can get hectic. Here at Pragmatic Works, we’re no different. But one of our goals is to learn something new about Azure every day, as things are constantly changing and being updated. Many people are still learning all the amazing things they can do within the Azure cloud and we want to help. Our posts in our Azure Every Day series are a great way to learn more about Azure each week.

There are many options for data storage, how do you know which is right for your data? Today I’d like to discuss storage in relation to the architecture of the modern data warehouse and to shed some light on your options.



Tom WardAzure Storage Options
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Event Driven ELT


Want to learn more about event driven ELT? Extract, Load, Transform (ELT) is a process where data is extracted for the source, then loaded into a staging table in the database, transforming it where it sits in the database and then loading it into the target database or data warehouse. In a recent webinar, Principal Consultant Michael French, gives a practical demonstration of how to move data from Azure Blob Storage to an Azure SQL Database using Azure Data Factory and Logic Apps.

Tom WardEvent Driven ELT
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Azure Data Factory v2 Parameter Passing: Linked Services

icon_azure@2xSometimes I get so involved in my repeatable processes and project management that I forget to look up.  Such is the case of the December 2018 ability to parameterize linked services.  I could not rollback and rework all the ADF components this impacted which had already gone to production, but oh hooray!  Moving forward, we can now have one linked service per type, one dataset per linked service and one pipeline per ingestion pattern.  How sweet is that?  Au revoir to the days of one SSIS package per table destination.  

This is blog post 3 of 3 on using parameters in Azure Data Factory (ADF).  Blog post #1 was about parameterizing dates and incremental loads.  Blog post #2 was about table names and using a single pipeline to stage all tables in a source.  Today I am talking about parameterizing linked services.

Disclaimer: Not all linked service types can be parameterized at this time.  This feature only applies to eight data stores:

  • Azure SQL Database
  • Azure SQL Data Warehouse
  • SQL Server
  • Oracle
  • Cosmos DB
  • Amazon Redshift
  • MySQL
  • Azure Database for MySQL

Concept Explained:
The concept is pretty straightforward and if our  goal is to have one linked service per type, a parameterized Azure SQL Database linked service might look like this:

Tom WardAzure Data Factory v2 Parameter Passing: Linked Services
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