Load data into Azure SQL
After a database or instance is deployed, verified, and configured, the next logical step is to bring in data.
Options
Many options are available for loading data into Azure SQL. Some overlap with what's available on-premises. This unit calls out a few.
Bulk Copy Program
Bulk Copy Program (bcp) is a common tool for connecting to Azure SQL from on-premises, and for connecting to Azure SQL from an Azure virtual machine. You can then use it to move data into Azure SQL.
Bulk insert
Bulk insert operations are similar to what's available in SQL Server on-premises. But instead of loading data from a file or multiple files on your machine, you load data from Azure Blob storage. The next exercise walks through an example of how.
SSIS packages
In Azure SQL, you can use packages to connect with SQL Server Integration Services (SSIS) on-premises. You can host an SSIS database in Azure SQL Database or Azure SQL Managed Instance. Additionally, you can use the Azure-SSIS Integration Runtime for SSIS packages with tools like Azure Data Factory.
Other options
Other interesting options include using technologies like Spark or Azure Data Factory to load data into Azure SQL Database or Azure SQL Managed Instance. Though not directly related to loading, it's possible to create a database by using an existing database for a copy or doing an import of a BACPAC file. In Azure SQL Managed Instance, you can use T-SQL commands to restore a database natively from a URL.
Considerations for loading data
The biggest difference between loading data on-premises and loading data into Azure SQL is that the data you want to load needs to be hosted in Azure. The data can't be hosted in files on-premises. You can store the on-premises files and file systems in Azure Blob storage as an alternative. This strategy also increases your efficiency in loading your files in and setting up ETL jobs.
Also keep in mind that minimal logging isn't supported, so you're always running in full recovery mode. Because of full recovery mode and limits around log throughput, log governance might have an effect as you load data. Techniques like using batches and appropriately sizing them become important during a bulk load. There are more tips in the following exercise. Loading into a clustered columnstore index might help in avoiding transaction log limits, depending on your scenario.