COMPARISON GUIDE
Microsoft Fabric vs Databricks vs Snowflake
Three leading data platforms, three different philosophies. Here's how they compare, and how to choose the right one for your organisation.
Microsoft Fabric, Databricks and Snowflake can all power a modern data platform, from data engineering to analytics and AI. They overlap a lot, but each starts from a different place: Fabric from an all-in-one Microsoft experience, Databricks from data engineering and machine learning, and Snowflake from an easy-to-run cloud data warehouse.
The right choice depends less on features and more on your existing technology, your team's skills, how you want to pay and what you plan to do with your data.
DATA LEAGUE is a consulting partner of Databricks and Snowflake, and also delivers Microsoft Fabric solutions. We work with all three platforms, so this guide aims to be practical and balanced.
Side-by-Side Comparison
| Feature | Microsoft Fabric | Databricks | Snowflake |
|---|---|---|---|
| What it is | An all-in-one SaaS analytics platform covering data integration, engineering, warehousing, real-time analytics and Power BI | A data intelligence platform built on Apache Spark and the lakehouse architecture | A cloud data platform with separate storage and compute, known for its easy-to-run data warehouse |
| How it's delivered | Fully managed SaaS on Microsoft Azure | Managed platform running in your cloud account, with serverless options | Fully managed SaaS |
| Clouds | Azure, with shortcuts to data in other clouds | Azure, AWS and Google Cloud | Azure, AWS and Google Cloud |
| Storage | OneLake, using open Delta Parquet format | Delta Lake, an open format | Managed storage, plus support for Apache Iceberg tables |
| Pricing model | Capacity-based: you buy a capacity size, pay-as-you-go or reserved, plus storage | Consumption-based: Databricks units plus the underlying cloud compute, or serverless | Consumption-based: credits for compute, billed per second, plus storage |
| Best suited skills | Power BI, SQL and low-code users, plus notebooks for engineers | Data engineers and data scientists using Python, Spark and SQL | SQL-focused data teams |
| Business intelligence | Power BI built in, including Direct Lake mode | Built-in dashboards, plus connectors for Power BI and Tableau | Connectors for Power BI, Tableau and other BI tools |
| AI and machine learning | Copilot, data science notebooks and Azure AI integration | The most extensive ML tooling: MLflow, model serving and AI agent frameworks | Built-in AI functions and Snowpark for Python-based ML |
| Governance | Microsoft Purview integration and the OneLake catalog | Unity Catalog | Built-in governance and security features (Snowflake Horizon) |
Which Platform Should You Choose?
Choose Microsoft Fabric if…
- You already use Microsoft 365, Power BI and Azure
- You want one platform and one bill for everything
- Your team is strongest in Power BI and SQL
- You want to get started quickly, with minimal setup
Choose Databricks if…
- Data engineering and machine learning are central to your plans
- You need to run on AWS or Google Cloud, or across clouds
- You have strong Python and Spark skills, or want to build them
- You process very large or complex data at scale
Choose Snowflake if…
- You want a powerful, low-maintenance data warehouse
- Your team works mainly in SQL
- You need to share data securely with partners or customers
- You want to pay for compute only while queries run
Can You Use Them Together?
Yes, and many organisations do. Fabric can bring in data from Databricks and Snowflake through mirroring and shortcuts, so Power BI users can work with it without copying everything. Databricks and Snowflake both connect to Power BI and Tableau, and all three support open table formats that make data easier to share.
The best architecture is usually the simplest one that meets your needs. Our Fabric Accelerator, Databricks and Snowflake teams can help you design it.
Want a recommendation for your organisation?
Every organisation is different. We'll look at your data, skills and budget and give you an honest recommendation.
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