SSIS

Traditional data integration solutions like SSIS, Talend, and Informatica have long been foundational pillars of the ETL approach, with widespread deployments across enterprise information systems. Their structure enables precise data extraction and transformation before loading, a robust model well-suited for environments where data processing must be performed internally for governance or compliance reasons.  

However, the rapid evolution of data architectures, particularly the rise of cloud data warehouses, has introduced a paradigm shift with the ELT approach. In this model, data is loaded directly into the warehouse, where transformations are then performed, typically using modern solutions such as BigQuery, Snowflake, or Databricks. This reduces data movement, improves efficiency, and optimizes processing times, making it particularly well-suited for big data and cloud-native environments.  

While traditional ETL solutions with SSIS, Talend, and Informatica may seem outdated, they remain relevant. These tools, deeply embedded as legacy systems in many organizations, are essential for complex workflows and offer a level of resilience that is difficult to match.  

MDN’s point of view  

It is recommended to test these tools in context despite their limitations compared to newer ELT solutions. Placing them in the "Trial" category encourages a gradual transition approach: teams can maintain these traditional solutions while considering parallel integration of ELT technologies for use cases requiring flexibility and scalability.