Overview
Organizations modernizing their data ecosystems now manage data flowing from cloud applications, SaaS platforms, on-premises systems, and streaming sources. Traditional ETL tools such as SQL Server Integration Services (SSIS) have long powered enterprise data warehousing and batch integration, offering a robust, code-optional environment for building data workflows. SSIS provides a Windows-based, SQL Server-centric platform for extracting, transforming, and loading data using visual design tools, built-in connectors, and highly customizable task orchestration.
Microsoft Fabric introduces a different approach with Fabric Data Factory, a cloud-scale, fully managed data integration experience built on top of the unified Fabric platform. As the next evolution of Azure Data Factory, Fabric Data Factory offers more than 170 connectors, AI-assisted transformations, hybrid connectivity, and seamless integration with OneLake, making it suitable for modern cloud-first analytics and distributed architectures.
Rather than relying on a single on-premises integration engine, organizations now align workloads to cloud-native services that scale elastically, integrate across multicloud environments, and unify data ingestion with analytics and AI capabilities.
Key Differences Between SSIS and Fabric Data Factory
Architecture and Deployment Model
SSIS
- Installed and executed on Windows servers as part of SQL Server.
- Designed primarily for on-premises workloads, with optional execution in Azure Data Factory through the SSIS Integration Runtime.
- Workflows are built in SQL Server Data Tools using drag-and-drop components and optionally extended with .NET code.
Fabric Data Factory
- Fully cloud native, running inside Microsoft Fabric’s SaaS environment.
- Removes infrastructure management and provides elastic scaling for pipelines, dataflows, and transformations.
- AI-driven orchestration and unified integration with OneLake and Fabric’s analytics workloads.
Data Integration Capabilities
SSIS
- Strong ETL engine with extensive built-in transformations, data cleansing functions, and workflow automation tasks.
- Well suited for SQL Server ecosystems and structured data movement.
- Supports many sources including files, XML, and databases, but connectors and cloud-native capabilities are limited.
Fabric Data Factory
- Connects to more than 170 data sources including multicloud and hybrid systems via gateways.
- Supports ETL and ELT using pipelines, dataflows, Power Query transformations, and AI-assisted mapping.
- Integrated transformation capabilities make it easier to prepare data directly for Lakehouse or Warehouse consumption.
Scalability and Performance
SSIS
- Scaling requires provisioning additional on-prem machines or SSIS IR nodes when running in Azure.
- Best suited for batch-oriented workloads with predictable throughput.
Fabric Data Factory
- Automatically scales pipeline execution without user-managed infrastructure.
- Built for high-volume, cloud-scale ingestion and transformation across distributed environments.
Cloud Ecosystem Integration
SSIS
- Deeply integrated with SQL Server, SQL Agent, and on-prem Windows environments.
- Cloud integration is possible but not inherent and often depends on Azure Data Factory hosting or custom connectors.
Fabric Data Factory
- Natively integrated into the broader Fabric ecosystem: OneLake unified storage, Lakehouse and Data Warehouse workloads, real-time analytics, and governance.
- Enables end-to-end analytics without switching platforms.
User Experience and Development Approach
SSIS
- Uses a Visual Studio-based designer focused on data engineers.
- Supports complex control flows, custom scripting, and rich debugging within SQL Server Data Tools.
Fabric Data Factory
- Web-based, low-code and no-code environment integrated with Power Query, making transformation accessible to both analysts and engineers.
- AI-assisted capabilities help accelerate mapping, transformation, and error reduction.
Use Case Alignment
SSIS Is Best When:
- Workloads are primarily on-premises and SQL Server focused
- Organizations rely on complex control flows or custom scripts
- Existing SSIS packages need to continue running with minimal redesign
Fabric Data Factory Is Best When:
- Organizations want cloud-native, scalable data integration
- Data originates across SaaS, APIs, cloud platforms, and hybrid sources
- Teams need unified ingestion, transformation, governance, and analytics across the Fabric platform
- Business users and analysts participate in data shaping using Power Query
Final Thoughts
SSIS and Fabric Data Factory represent two generations of Microsoft’s data integration technology, each optimized for different environments. SSIS remains a powerful and mature ETL engine for on-premises SQL Server workloads, offering granular control, rich transformations, and a familiar developer-centric experience. Fabric Data Factory, built into the modern Fabric ecosystem, provides a cloud-first, scalable, AI-enhanced integration environment designed for distributed systems, multicloud data movement, and unified analytics.
Choosing between the two is not about replacing one with the other. It is about selecting the right tool for your data landscape. SSIS continues to serve organizations with established SQL Server ecosystems, while Fabric Data Factory meets the needs of cloud-native, analytics-driven architectures.
If you would like to discuss your own integration challenges, modernization strategy, or migration considerations, feel free to reach out to me on LinkedIn.
For more information, explore Microsoft’s official documentation: