Azure Data Factory is suitable for the following
Posted: Wed Jan 22, 2025 4:47 am
Data migration scenarios:
Migrate your big data workload from Amazon Simple Storage Service (Amazon S3) or an on-premises Hadoop distributed file system (HDFS) to Azure.
Migrating EDW from Oracle Exadata, Netezza, Teradata and Amazon Redshift to Azure.
Advantages of data migration
Azure Data Factory has several advantages for data migration , including:
You can move petabytes of data for data lake migration and tens of terabytes of data for data warehouse migration.
You can easily scale the amount of processing denmark telegram data power needed to move data in serverless mode with high performance, resiliency, and scalability. And you pay only for what you use.
It has no limitations regarding data volume and number of files.
You can utilize your entire network and storage bandwidth to achieve the highest data movement performance in your environment.
You can perform a one-time historical load as well as a scheduled incremental load.
Use Azure Integration Runtime (IR) to move data between publicly accessible data lake endpoints and the data warehouse. You can also use self-hosted IR to move data between data lake and data warehouse endpoints located within an Azure virtual network or behind a firewall.
It has enterprise-grade security: You can use Windows Installer (MSI) or Service Identity for secure integration between services, or take advantage of Azure Key Vault for credential management.
integrated dashboard.
Migrate your big data workload from Amazon Simple Storage Service (Amazon S3) or an on-premises Hadoop distributed file system (HDFS) to Azure.
Migrating EDW from Oracle Exadata, Netezza, Teradata and Amazon Redshift to Azure.
Advantages of data migration
Azure Data Factory has several advantages for data migration , including:
You can move petabytes of data for data lake migration and tens of terabytes of data for data warehouse migration.
You can easily scale the amount of processing denmark telegram data power needed to move data in serverless mode with high performance, resiliency, and scalability. And you pay only for what you use.
It has no limitations regarding data volume and number of files.
You can utilize your entire network and storage bandwidth to achieve the highest data movement performance in your environment.
You can perform a one-time historical load as well as a scheduled incremental load.
Use Azure Integration Runtime (IR) to move data between publicly accessible data lake endpoints and the data warehouse. You can also use self-hosted IR to move data between data lake and data warehouse endpoints located within an Azure virtual network or behind a firewall.
It has enterprise-grade security: You can use Windows Installer (MSI) or Service Identity for secure integration between services, or take advantage of Azure Key Vault for credential management.
integrated dashboard.