Azure Data Factory vs SAS/Access

If you are just getting started and all your data is resident in the Azure cloud, then Azure Data Factory is likely to work fine without having to jump through too many hoops. However, in a hybrid environment (which is most of them these days), ADF will likely need a leg up. It works well for scheduling and basic scheduling/orchestration tasks, but the feature set is not at a level with SSIS (which has been around for 15 years so...). As ADF now supports deploying SSIS, it is also a good candidate if large amounts of your data are resident in the Azure cloud and you have an existing SSIS investment in code and licensing. We are using it in a hybrid fashion for the data warehouse and will slowly transition over to ADF as the feature set improves. We are also using it for cloud-native applications that only require supplemental data from on-prem resources

SAS/Access is well suited for companies who need to manipulate and analyze large databases and data-sets. It does the same thing as SQL, and if you already know basic SAS coding it is easier to pick up. SAS/Access works well with analyzing data from multiple data-sources at once, including large databases stored in external and virtual environments like Hadoop. Data can be easily reassembled from relational databases for use by the user. SAS/Access is not necessary if you are only pulling data from one database that you have the physical file for.

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

I have always received excelled service working with SAS technical support. Additionally, the tool is used so widely that there are many online resources and use cases that allow you to see many other uses or support routes.