22-25 April 2026 
Databricks vs Fabric: When to choose, when to combine, and why it’s confusing
Regular 50 minute session for SQLBits 2026TL; DR
Join this session to move beyond opinions and slide decks. Through practical demos, you’ll see how both platforms behave when solving the same real-world problems, and where the differences actually matter in delivery.
Session Details
Unsure whether Databricks or Microsoft Fabric is the right platform for your analytics stack?
Join this session to move beyond opinions and slide decks. Through practical demos, you’ll see how both platforms behave when solving the same real-world problems, and where the differences actually matter in delivery.
In this fast-paced, demo-driven session, we cut through the marketing noise and compare Databricks and Fabric across core analytics scenarios, from data engineering and governance to BI and AI workloads. Rather than listing features, we expose the trade-offs that only become visible once teams start building and operating these platforms at scale.
Key session takeaways:
- Where Databricks is objectively the stronger choice today
- Where Fabric simplifies architecture and accelerates delivery
- The compromises teams only uncover when delivery begins
- When using both together is not only viable, but the best option
This session is ideal for architects, data engineers, and technical decision-makers who need to justify platform choices to stakeholders and avoid costly re-platforming mistakes. You’ll leave with a clear mental model, practical decision criteria, and the confidence to explain why one platform, or a hybrid approach, is right for your organisation.
Join this session to move beyond opinions and slide decks. Through practical demos, you’ll see how both platforms behave when solving the same real-world problems, and where the differences actually matter in delivery.
In this fast-paced, demo-driven session, we cut through the marketing noise and compare Databricks and Fabric across core analytics scenarios, from data engineering and governance to BI and AI workloads. Rather than listing features, we expose the trade-offs that only become visible once teams start building and operating these platforms at scale.
Key session takeaways:
- Where Databricks is objectively the stronger choice today
- Where Fabric simplifies architecture and accelerates delivery
- The compromises teams only uncover when delivery begins
- When using both together is not only viable, but the best option
This session is ideal for architects, data engineers, and technical decision-makers who need to justify platform choices to stakeholders and avoid costly re-platforming mistakes. You’ll leave with a clear mental model, practical decision criteria, and the confidence to explain why one platform, or a hybrid approach, is right for your organisation.
3 things you'll get out of this session
Understand the real strengths and limitations of Databricks and Fabric through side-by-side demos
Apply a clear decision framework to choose the right platform or combination
Avoid common platform selection mistakes that lead to rework, cost, and re-platforming
Apply a clear decision framework to choose the right platform or combination
Avoid common platform selection mistakes that lead to rework, cost, and re-platforming
Speakers
Richard Conway's previous sessions
Performance Optimization with Azure Databricks
Azure Databricks has become one of the staples of big data processing. See how to make the most of it by understanding how Spark works under the covers.
Machine Learning at Scale with Apache Spark
Richard will show you, from no knowledge of Spark, how to navigate the Spark framework ecosystem and build complex batch and near real time applications that use Spark's machine learning library mllib
