Databricks vs Fabric: Which Should You Choose?
Clients ask me this weekly: “Should we use Databricks or Fabric?” My answer: It depends. Let me explain.
The Context
Both are data platforms. Both do analytics. Both integrate with Azure. But they’re optimized for different scenarios.
When Databricks Wins
Advanced ML workflows. If machine learning is core to your business, Databricks is purpose-built for this.
Multi-cloud needs. Works across Azure, AWS, GCP. Fabric is Azure-only.
Data science teams. Better notebooks, better collaboration, better ML tooling.
Complex streaming. Structured streaming capabilities are more mature.
Unity Catalog. Superior data governance across clouds.
When Fabric Wins
Power BI users. Direct Lake mode integration is game-changing.
Microsoft ecosystem. Everything integrates naturally with other Microsoft services.
Simpler use cases. Business intelligence, reporting, basic analytics.
Lower complexity. Single platform, unified experience, less to learn.
Cost for BI workloads. Can be cheaper for heavy Power BI usage.
Side-by-Side Comparison
| Feature | Databricks | Fabric |
|---|---|---|
| ML Focus | Excellent | Growing |
| BI Focus | Good | Excellent |
| Multi-cloud | Yes | No (Azure only) |
| Notebooks | Superior | Good |
| SQL Analytics | Good | Good |
| Real-time | Mature | Improving |
| Learning curve | Steeper | Gentler |
| Cost | Varies | Varies |
My Decision Framework
Choose Databricks if:
- ML is critical to your business
- You need multi-cloud
- Data science team is your primary user
- You value best-in-class notebooks
- Streaming analytics is core
Choose Fabric if:
- Power BI is your primary BI tool
- You’re heavily invested in Microsoft
- BI analysts are your primary users
- You want simplicity over flexibility
- You’re Azure-only
The Hybrid Approach
Some clients use both:
- Databricks for ML and complex data engineering
- Fabric for BI and reporting
- Data shared via Delta Lake
This works but adds operational complexity.
What I Usually Recommend
For data science teams: Databricks For BI teams: Fabric For mixed teams: Start with one, evaluate later
Don’t overthink it. Both are good platforms. Pick based on your primary use case and team skills.
The Bottom Line
There’s no universal “better” choice. There’s the better choice for YOUR situation.
Understand your requirements, know your team, evaluate both, then decide.
And remember: you can change later if needed. Don’t let analysis paralysis stop you from starting.