Parameters Azure Data Factory (ADF) SSIS
Overview Azure’s cloud ETL service for scale-out serverless data integration and data transformation An on-premises tool for creating enterprise-level data integration and data transformation solutions
Azure Data Factory Vs. SSIS Performance It is swift in performance since it works with the cloud-based architecture. Very fast in performance, data transformation is done in memory buffers
Variety of Data Structured and unstructured data Structured data
Programming Languages ADF does not have a programming SDK – It uses PowerShell, Python, and .NET SSIS has a programming SDK that uses automation through C#, BIML, VB
Development Tools Web browser SQL Server development tools
Costing Structure Abides by the ‘pay as you go’ model It has free and paid licensed versions
Utilization ETL, ELT, data movement, orchestration, Reverse ETL, streaming ETL, ELT, data integration, data transformation, Reverse ETL
Database Replication Full and incremental load Full and incremental load
Addition of New Data Sources Offers SDK for creating custom connectors By coding custom data source elements
Data Connectors Over 90+ inbuilt data connectors for data integration Various data connectors are compatible with .NET, ADO, ODBC, OLEDB, etc.
Developer Tools Azure Portal, CLI, PowerShell, Visual Studio Visual Studio, SQL Server Management Studio
Purchase Details Self-service purchase via Azure portal or Microsoft sales team Bundled along with Microsoft SQL Server
Version Control It can be integrated into Azure DevOps git or GitHub and supports branching, merging, etc. It can be integrated with TFS and Git, supporting team-based development with merging and branching.
Velocity of Data Streaming, real-time, and batch Batch
Data Flows It uses Apache Spark with optimization features, which makes it suited for more extensive data sets. Best suited for small to medium data sets because the startup time is more than the runtime
Learning Curve It is still evolving; hence, it needs time to master Since it has been around for a while, it is easy to learn
Support for Triggers ADF supports scheduled batch, event-based, and tumbling window triggers SSIS supports batch triggers only but can help in developing custom triggers for data streams
Data Integration It integrates with various cloud-based tools and other data sources like Azure Data Lake Store. Integrates with a range of connectors, though they may not be cloud-based
User Interface An effective graphical user interface for designing workflows executable in the cloud or on-premises Graphical interface with drag-and-drop components for the creation of pipelines
Architecture Hosted entirely in the cloud, networks are stateless On-premises tool that executes in the data center