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Data virtualization in SQL Server is a data integration approach that allows you to seamlessly connect, fetch, and manipulate data from multiple disparate sources. This technique has gained significant popularity among enterprise-level organizations due to its ability to provide a real-time, unified view of business data.
In this post, we’ll dive into SQL Server data virtualization and looking at how you can integrate data sources using SQL code.
The Concept of Data Virtualization
Data virtualization hinges on the concept of providing a single interface to access data from multiple sources, irrespective of their location, format, or volume. This kind of abstraction from the physical data layer means users can query data from a ‘single source of truth’, without needing to know where or how the data is stored.
An Example of Query in SQL Server
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CREATE DATABASE TestDB USE TestDB CREATE TABLE Employees ( EmployeeID int, FirstName varchar(255), LastName varchar(255), Address varchar(255), City varchar(255) ) |
The above SQL Server code will create a ‘TestDB’ database and an ‘Employees’ table within that database.
Data Virtualization in SQL Server
SQL Server implements data virtualization through PolyBase – a technology that allows SQL Server to execute Transact-SQL queries that integrate data from external sources. PolyBase uses the same SQL syntax, making it easy to pull data from various sources directly into your SQL Server environment.
Establishing External Data Sources
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CREATE EXTERNAL DATA SOURCE MyAzureBlobStorage WITH ( TYPE = HADOOP, LOCATION = 'wasbs://[container]@[storage_account].blob.core.windows.net', CREDENTIAL = MyAzureBlobStorageCredential ) |
This SQL Server code creates an external data source pointing to an Azure Blob Storage account. Here, ‘MyAzureBlobStorage’ is the name given to our data source.
Final Thoughts
Data integration and SQL Server data virtualization using PolyBase is a powerful way to maximize data availability and security across your organization. This technical method of centralizing data access points requires a sound understanding of SQL and data manipulation techniques.
As we’ve seen with our SQL Server code examples, the process is entirely executable, giving you a real-time, consolidated view of your business data from different sources.