Microsoft Fabric and Databricks are often presented as rivals, and they do compete for the same budget. But they were built from opposite ends. Fabric starts from Power BI and Microsoft 365 and adds data engineering around it. Databricks starts from Apache Spark and machine learning and adds analytics on top. This guide compares them as of November 2026, using current prices and features, so you can decide which fits your team, or whether you need both.
Two different ideas of a data platform
Microsoft Fabric
All-in-one SaaS- Storage
- OneLake, one lake per organisation
- Compute
- shared capacity units (F2 to F2048)
- Cloud
- Azure only
- AI
- Copilot, Fabric data agents
- Power BI built in, with Direct Lake for fast reports on lake data
- Familiar to Excel, Power BI and SQL Server teams
- Fewer machine learning features, no GPU Spark pools
Best for Microsoft-first companies where Power BI is the main output.
Databricks
Lakehouse platform- Storage
- Delta Lake and managed Iceberg in your cloud storage
- Compute
- per workload, billed in DBUs
- Cloud
- AWS, Azure and Google Cloud
- AI
- Agent Bricks, Genie, Model Serving
- Strongest for data engineering, machine learning and AI agents
- Open formats and multi-cloud
- More to set up and govern; BI is not the core product
Best for engineering-heavy teams building ML and AI on their data.
Pricing
The billing models are the biggest practical difference.
- Fabric capacity
- One pool of capacity units shared by every workload: $0.18 per CU-hour pay-as-you-go, about 41% cheaper with a reservation. An F2 is about $263 a month; an F64 about $8,410 a month pay-as-you-go, or about $5,003 reserved.
- Fabric and Power BI licences
- Report authors always need a Power BI licence. Below F64, viewers also need one; from F64 up, viewers with free licences can read reports.
- Databricks DBUs
- Each workload, such as jobs, SQL warehouses, all-purpose clusters or model serving, has its own DBU rate. On classic compute you also pay your cloud provider for the virtual machines; serverless options include them.
- Storage
- Fabric charges for OneLake storage; Databricks data sits in your own cloud storage, billed by your cloud provider.
Power BI and analytics
If your organisation lives in Power BI, Fabric is hard to beat. Direct Lake lets Power BI read tables straight from OneLake without importing them, and Copilot works across reports, notebooks and the warehouse. Databricks has its own dashboards and Genie, natural-language analytics for business users, but most Databricks customers still use Power BI or another BI tool on top.
Machine learning and AI agents
| Microsoft Fabric | Databricks | |
|---|---|---|
| Model training | Spark notebooks with ML libraries; no GPU Spark pools | GPU compute, MLflow, managed feature store |
| Serving models | Limited; usually through Azure AI services | Model Serving and Unity Gateway for many model providers |
| Agents | Fabric data agents and Copilot for business users | Agent Bricks and Genie Code; ChatGPT, Claude and Cursor can connect to Databricks MCP servers |
| Business context | Power BI semantic models | Metric views, now with relationships between them (beta) |
Open formats and lock-in
Both store data in open Delta Parquet files, which helps. Databricks offers read-write managed Apache Iceberg tables and runs on three clouds. Fabric reads Iceberg through shortcuts, with its Iceberg REST APIs still in preview, and runs only on Azure. If keeping your options open matters, Databricks has the edge.
The "both" pattern
Many companies now let engineers work in Databricks and business users work in Fabric and Power BI, linked by mirroring rather than copies. It costs two platforms, but each team gets the tool it is best at.
How to choose
- 1
Start from your main output
If most work ends in Power BI reports, start with Fabric. If it ends in pipelines, models and AI apps, start with Databricks.
- 2
Check your cloud
Fabric needs Azure. If you are on AWS or Google Cloud, Databricks avoids moving data.
- 3
Count your users
From F64, Fabric lets free users view Power BI reports, which changes the maths for large audiences.
- 4
Model the bill
Estimate a month of real workloads on both. Capacity versus pay-per-use can swing the result either way.
- 5
Consider both
If you already have Azure Databricks, mirroring into Fabric for Power BI is often the simplest answer.
Check your understanding
1/3How does Microsoft Fabric bill compute?
Fabric capacity is $0.18 per CU-hour pay-as-you-go, shared across all workloads.
2/3From which Fabric size can viewers with free licences read Power BI reports?
Below F64, viewers also need a paid Power BI licence.
3/3What links Azure Databricks and Fabric without copying data?
Mirroring is generally available and lets Power BI use Direct Lake on Databricks tables.
You got 0 out of 3.
More comparisons: Power BI vs Tableau, BigQuery vs Snowflake and Snowflake vs Databricks for AI agents. Recent news: FabCon Europe 2026 and the Databricks October 2026 update.
Sources: Brickster's sourced comparison of Databricks and Microsoft Fabric (pricing from July 2026, features verified September 2026); Microsoft Fabric and Power BI licensing documentation; Databricks release notes (October and November 2026). Prices are pay-as-you-go US list prices and change; check both vendors before deciding.
Alessandro Ecclesie AgazziWritten by Alessandro Ecclesie Agazzi, analytics engineer in London. Updated 3 November 2026. About me