Insights | Technology Services

Get Your Head In the Clouds – A Pragmatic Approach for Migrating to an Azure Cloud Data Platform

Moving to an Azure SQL server doesn't have to include a mass overhaul of your existing data architecture.

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Author: Corey Biehl


For many organizations, digital transformation continues to have a significant role in keeping up with the competition, let alone attempting to gain a competitive advantage. In the world of data and analytics, the cloud plays a major role in this transformation. And, for those that run Microsoft SQL Server on-premise for their data management infrastructure and architecture, this digital transformation is creating new challenges in security policy management, increased license costs, and infrastructure overhead when attempting to stay the course with an existing tech stack.

As Microsoft continues to focus its efforts and investments into its cloud platform and associated services, the support for customers running legacy software on on-premise servers will continue to diminish. This puts companies at a data management strategy crossroads: continue to maintain and build off legacy on-premise database technology or advance into the cloud (e.g., Microsoft Azure) for future growth and scalability.

Some organizations are hesitant to make this migration to the cloud, believing that it must come with a full-scale refactoring of their existing data architecture. We intend to put you at ease by providing the initial pragmatic options for entry into the realm of cloud data management without mass overhaul.

Once in the cloud, the unbounded possibilities inherent to the more progressive data and analytics services available will come in due time – when your organization is at the right stage of maturity in your digital transformation journey. To that end, this article will focus on migrating from an on-premise SQL Server to Azure SQL Server and provide insights that will help breakdown two of its most popular services and “as a service” options.


Practical Considerations

The cloud can be a daunting place for those that first experience it. There are a multitude of services that can quickly overwhelm even the most experienced data professionals; some Azure database services Microsoft currently provides are:

  • Azure SQL
  • SQL Server Virtual Machine (VM)
  • Postgres
  • MySQL
  • Cosmos
  • Synapse

So, which is right for your organization? We will explore the differences of these services in a later article. The good news is that you don’t have to become well versed in all these services overnight to move to an Azure cloud data platform.

A pragmatic approach to moving from on-premise to Azure can be much less complicated than it may appear. Don’t reinvent the wheel if your use cases don’t support it (yet). Many of the same things being done on-premise for data management can be done similarly in Azure.

Take for example a traditional data management solution that resides on-premise using SQL Server Relational Database Management System & SQL Server Integration Services (SSIS). Source data is extracted using SSIS projects loaded into SQL and transformed into the appropriate data model for business use. For an initial low-lift move to Azure, the most practical “lift and shift” approach would be to either implement Azure SQL Database or using an Azure Virtual Machine (VM) running SQL Server. By using Azure Data Factory for data pipelines, your existing SSIS packages can be leveraged and still allow for development using Visual Studio SQL Server Data Tools (SSDT).

Azure SQL Database runs as a Platform as a Service (PaaS), significantly reducing your administration support needs (e.g., updates, patches, security, and maintenance), automatically providing high availability and ease of scalability as your data needs grow. Many of the same database features and standards apply in Azure.

However, it is pertinent to call out that there are a few non-supported features such as:

  • Simple/bulk recovery backups
  • DB Mail
  • Linked Servers
  • SQL Agent
  • 100 TB data ceiling

The tradeoff is a good one: four-nines uptime guaranteed, on-demand scalability, automated backup processes for both short- and longer-term storage, the reduced need for administration/hardware ownership, and the latest Enterprise Edition of SQL Server. These administrative reasons alone form a very compelling case to migrate to Azure SQL Database.


Other Azure Options

Not ready to concede that control yet? There is yet another option with Infrastructure as a Service (IaaS) running SQL Server on an Azure VM. This option is most similar to an on-premise implementation without the hardware considerations.

Running an Azure VM SQL Server environment provides the same levels of compatibility; you still get to perform all the server administration and OS upgrades, control of the database engine, and scheduling of maintenance activities. In addition, you also have the same recovery models as before. Models for full, simple, or bulk-logged backups. Also, you can start or stop the VM whenever needed.

Once established in Azure, the possibilities to improve upon your data management strategy begin to really take hold. Think Synapse Analytics, Databricks, Azure Machine Learning, etc. The list of advanced services seems countless. As your organization grows, so will the need to apply different data management solutions in your already existing Azure cloud data platform. This allows your team to strengthen and learn as you evolve into the cloud’s possibilities and apply those different applications over time versus having to design and manage an entirely new data management environment from the onset.

Let us help your organization take that first step by moving your data management into Azure’s cloud data platform. Unsure if Azure is the right fit for your organization? Review our comprehensive Agile Cloud Foundation or contact us to schedule a quick chat with one of our cloud data management experts.



Corey Biehl is a technology leader in RevGen’s analytics and insights practice. He is passionate about designing and developing data & analytic solutions that make a difference.



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