Differences and similarities between Azure Data Factory and Synapse Analytics.
Azure Data Factory and Azure Synapse Analytics are two very similar services, that provide visual data integration from many sources. Working with Synapse you can have full compatibility with both solutions, but which one is more suitable for you? In this article I will compare both services and try to help you make a decision.
Let us start with a brief definition of both services. In Microsoft's documentation we can find the following descriptions:
Azure Synapse Analytics (ASA) is an unlimited analytical service, that combines data integration, data warehousing, and big data analytics. It gives you the freedom to perform data queries on your terms, using serverless or dedicated resources - on a large scale. Azure Synapse service connects these worlds together in a unified environment that enables you to acquire, explore, prepare, transform, manage, and share data for immediate business analytics and machine learning.
Azure Data Factory (ADF) is a cloud-based ETL service on the Azure platform, allowing for scalable serverless data integration and data transformation. It offers a code-less user interface for intuitive creation and monitoring and management with a single service. You can also migrate existing SSIS packages to the Azure platform and run them with full compatibility with ADF. SSIS Integration Runtime offers a fully managed service so you don't have to worry about managing your infrastructure.
In summary, the ASA service, like ADF, offers codeless data integration capabilities. You can easily build data integration pipelines using its graphical interface. In addition, Synapse allows you to build pipelines containing scripts and complex expressions to solve advanced ETL scenarios, with ADF giving us the ability to use SSIS packages.
Synapse Analytics is based on a similar concept to Data Factory. Most of the actions that ADF allows us to perform can also be done in ASA. Despite the many features of both services, they also have a few differences. In Synapse, we will experience new features, a lack of some of the solutions available in the Factory, but also features that both environments have, but work slightly differently.
The main difference is that SSIS Integration Runtime is provided in ADF, which is not found in its twin:
Synapse has Spark notebooks, Spark jobs, and SQL pool stored procedures that are not available in ADF. The Factory only gives us the ability to use Databricks notebooks.
Another difference we can notice is that Continuous Integration (CI) and Continuous Delivery (CD) cannot be integrated with GitHub service; they are not part of the Azure Synapse service user interface.
At first, Synapse lacked the functionality that we had for a long time in ADF - creating a pipeline from a template. Additionally, in the November update, ASA got the option to create a database using a template gallery.
In Microsoft's documentation, we can find the following table, which gives us an overview of the basic differences between ADF and Synapse Analytics and will be a good summary:
Robert Hauzer
Data Engineer