Forum Discussion
microsoft fabrics and databricks
If i do microsoft fabrics , do i still need to learn databricks and is databricks included in fabrics or just doing fabrics is enough?
It depends on your career goals, but in general learning Microsoft Fabric first is a great foundation.
Databricks is not included in Microsoft Fabric. Fabric has its own Spark-based experience (Fabric Data Engineering and Data Science) that lets you work with notebooks, Spark jobs, Delta tables, and lakehouses without requiring Databricks.
If you're working mainly in the Microsoft ecosystem (Power BI, Fabric, Azure), Fabric is often sufficient for many analytics, BI, and data engineering workloads.
Databricks is still worth learning if you expect to work in organizations that use multi-cloud environments (AWS, Azure, GCP), large-scale data engineering, advanced ML, or already have an established Databricks platform.
So the learning path I'd recommend is:
Master Microsoft Fabric.
Learn Spark fundamentals (these transfer to Databricks).
If your role or employer requires it, pick up Databricks afterward—it will be much easier because many concepts (Spark, Delta Lake, notebooks, SQL) are shared.
In short: Fabric is enough to get started and build a strong career in the Microsoft data ecosystem, but learning Databricks later will broaden your opportunities rather than replace Fabric.
8 Replies
Hi Kudakwindima
I have been working with Fabric since its inception and there certainly is more than enough work and details in there to only stay on Microsoft Fabric. It is still good to know what Databricks capabilities are. They've been talking to people you can do a comparison!
thank you so much
Fabric is powerful enough to build a career around, especially if you're working in the Microsoft ecosystem. However, Databricks is a separate platform and is still worth learning since many organizations use it.
thank you
It depends on your career goals, but in general learning Microsoft Fabric first is a great foundation.
Databricks is not included in Microsoft Fabric. Fabric has its own Spark-based experience (Fabric Data Engineering and Data Science) that lets you work with notebooks, Spark jobs, Delta tables, and lakehouses without requiring Databricks.
If you're working mainly in the Microsoft ecosystem (Power BI, Fabric, Azure), Fabric is often sufficient for many analytics, BI, and data engineering workloads.
Databricks is still worth learning if you expect to work in organizations that use multi-cloud environments (AWS, Azure, GCP), large-scale data engineering, advanced ML, or already have an established Databricks platform.
So the learning path I'd recommend is:
Master Microsoft Fabric.
Learn Spark fundamentals (these transfer to Databricks).
If your role or employer requires it, pick up Databricks afterward—it will be much easier because many concepts (Spark, Delta Lake, notebooks, SQL) are shared.
In short: Fabric is enough to get started and build a strong career in the Microsoft data ecosystem, but learning Databricks later will broaden your opportunities rather than replace Fabric.
thank you for the clear explaination. this is very helpful
You're very welcome! I'm glad the explanation helped and that you found it useful.
Wishing you all the best on your Microsoft Fabric learning journey and in your data career. Good luck with your studies and future projects—I'm sure you'll do great. Happy learning! 🚀
Hi Kudakwindima,
Thank you for reaching out to Microsoft Fabric Community.
Thank you GilbertQ and Nawid for the prompt response.
As we haven’t heard back from you, we wanted to kindly follow up to check if the response provided by the user's for the issue worked? or let us know if you need any further assistance.
Thanks and regards,
Anjan Kumar Chippa
