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Classic SQL Cloud Platform vs. Data Lakehouse in Microsoft Fabric

As I gear up for our twoday kapacity seminar in Aalborg today, I’m thrilled to share some insights from my collaborative work with Klaus Guldberg Ulsøe. Together, we’ve compared the tried-and-true Classic SQL Cloud Data Platform against the emerging Data Lakehouse in Microsoft Fabric.


✅ Pros: Classic SQL Cloud Data Platform

  • Ideal for Traditional Workloads: Excellently suited for traditional data warehouse tasks.
  • Familiar Technology: Offers a minimal learning curve due to its well-known nature.
  • Mature Ecosystem: Features a robust range of tools and integrations.

❌ Cons: Classic SQL Cloud Data Platform

  • Limited Scalability: Struggles to scale efficiently beyond 16 cores of processing power.
  • Complex Incremental Updates: Managing incremental updates for semantic models can be intricate.
  • Lack of Automatic Scaling: Absence of auto-scaling for compute resources.
  • Restricted Data Accessibility: Challenges in accessing data across different environments.
  • Limited Data Science Capability: Inherent services for handling data science workloads are lacking.
  • No Support for Real-Time Streaming: Inadequate for real-time data streaming scenarios.

✅ Pros: Data Lakehouse in Microsoft Fabric

  • Versatile Data Handling: Capable of managing a wide range of data types.
  • Real-Time and Batch Processing: Efficiently handles both real-time and batch data processes.
  • AI and ML Integration: Integrated support for Artificial Intelligence and Machine Learning.
  • Unified Platform: Offers a single, cohesive solution including reporting.
  • Seamless Azure Integration: Easily integrates with the rest of Azure and Microsoft 365.
  • Direct Lake in Power BI: Eliminates the need for frequent compute intensive refreshes of semantic models.
  • Cost-Effective: Potential savings, especially for organizations with Power BI Premium.

❌ Cons: Data Lakehouse in Microsoft Fabric

  • Emerging Technology: Though promising, it’s a relatively new technology with an evolving landscape.
  • Initial Adoption Caution: Consider to start with Databricks and the transitioning as the technology matures.


Deciding between a Classic SQL Cloud Data Platform and a Data Lakehouse in Fabric hinges on your specific data needs and organizational context. If you prioritize familiarity and a mature ecosystem for traditional workloads, the Classic SQL Cloud is your go-to. However, for flexibility, real-time processing, and AI integration, the Data Lakehouse in Fabric presents an innovative path, especially for those already integrated into the Azure and Microsoft 365 ecosystems.

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