With Microsoft Fabric Microsoft has created a platform that is both Lakehouse as well as Data Warehouse integrated. Both terms are often used, but what exactly is behind them - and when is which model suitable?
Similarities
Central databaseBoth concepts are based on OneLake the central storage in Fabric.
Integration with Power BIBoth Lakehouse and Warehouse can be used seamlessly for reports.
SQL supportIn both approaches, data can be queried using SQL - a familiar approach for many analysts.
ScalabilityBoth systems use Fabric's cloud architecture, which allows computing power to be scaled flexibly.
Differences
| Feature | Lakehouse | Data Warehouse |
|---|---|---|
| Data structure | Can store unstructured, semi-structured and structured data (e.g. JSON, Parquet, CSV, ERP data) | Strictly structured data, optimized for tables and classic BI analyses |
| Flexibility | Very flexible, ideal for data science, AI, big data | More standardized, optimized for controlling & management reporting |
| Access | Data can be saved raw and transformed later | Only cleansed and structured data is available |
| Speed | Very good for large amounts of data, but transformations can take time | Optimized for fast SQL queries and KPIs |
| Target group | Data scientists, analysts, companies with many different data sources | Controllers, management, business analysts |
Advantages & disadvantages
✅ Lakehouse advantages
Universal: supported all data types.
Perfect for Data science and AI models.
No duplicate memory required - raw data remains available.
❌ Lakehouse disadvantages
For classic BI reports sometimes too flexible → higher modeling effort.
Performance for standard KPIs often lower than in the warehouse.
✅ Data warehouse advantages
Very high performance for SQL queries.
Structured KPIs (e.g. contribution margins, cash flow) are easy to calculate.
Specialist areas (e.g. controlling) can Get started right away, without complex modeling.
❌ Data warehouse disadvantages
Only for Structured data suitable.
Less flexible for data science or AI applications.
Transformations often have to previously defined become.
The Lakehouse is ideal if companies want to merge many different data sources (ERP, IoT, cloud, Excel, logistics) and also use them for AI analyses.
The Data Warehouse is the best choice when it comes to Structured reports and fast SQL queries especially in controlling or management.
👉 The big advantage of Microsoft Fabric: Companies do not have to decide. Both models work hand in hand - and that's what makes Fabric so strong.
Do you have any questions or would you like to find out more about our methods? Get in touch with us - We show you how you can use your data for sustainable success.