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As organizations move their data to the cloud, they are faced with the decision of choosing the right data integration tool. Two popular options are SQL Server Integration Services (SSIS) and Azure Data Factory (ADF). Both serve as ETL (Extract, Transform, Load) tools but have different features, functionality, and pricing models. This post will discuss some of the considerations when deciding between SSIS and ADF for ETL migration.

SSIS is a mature, on-premises ETL tool that comes bundled with Microsoft SQL Server 2019. It is ideal for organizations that wish to maintain control over their data and infrastructure. SSIS provides a wide range of transformations out of the box and includes a rich GUI for package design. However, it requires manual scaling and significant maintenance. Here's an example of an SSIS T-SQL script:

-- T-SQL script for SSIS
EXEC sp_addlinkedserver   
   @server='MyLinkedServer', 
   @srvproduct='',
   @provider='SQLNCLI', 
   @datasrc='\\network\path\myDataFile.csv',
   @provstr='Text';

On the other hand, Azure Data Factory is a cloud-based ETL and data integration service. It natively integrates with other Azure services like Azure SQL and Azure Synapse. Unlike SSIS, ADF is serverless, so it scales automatically and requires less management. It also supports a wider range of source and destination data stores, including non-Microsoft databases like MySQL 8.0 and IBM DB2 11.5. Here's an example of an ADF pipeline script:

-- JSON script for an ADF pipeline
{
  "name": "PipelineName",
  "properties": {
    "activities": [
      {
        "name": "CopyData",
        "type": "Copy",
        "inputs": [
          {
            "referenceName": "InputDataset",
            "type": "DatasetReference"
          }
        ],
        "outputs": [
          {
            "referenceName": "OutputDataset",
            "type": "DatasetReference"
          }
        ],
        "typeProperties": {
          "source": {
            "type": "Source"
          },
          "sink": {
            "type": "Sink"
          }
        }
      }
    ]
  }
}

Another significant difference between SSIS and ADF is their pricing models. SSIS is licensed as part of SQL Server, so there are no additional costs for using it. However, there are costs associated with the infrastructure needed to run SSIS. ADF follows a pay-as-you-go model, where you're charged based on the resources consumed.

In conclusion, both SSIS and ADF have their strengths and are suited to different scenarios. If you have a substantial on-premises footprint and primarily use SQL Server, SSIS might be a good fit. On the other hand, if your organization is moving towards a cloud-first approach and needs to integrate with a variety of data sources, ADF could be the better choice.