Microsoft Fabric vs. Databricks: how to choose

Microsoft Fabric and Databricks are often presented as direct competitors. Both support data engineering, analytics, and machine learning, but they are built around very different philosophies. This guide compares the two platforms to help you determine which one is the better fit for your organization.

Two different approaches

Microsoft Fabric is a fully managed SaaS platform designed for simplicity. There are no clusters to configure and no infrastructure to manage directly.

Databricks, on the other hand, is an open, multi-cloud platform that gives teams greater control over architecture and infrastructure, but with a higher level of operational complexity.

What each platform does best

Databricks remains a strong choice for large-scale data engineering, advanced machine learning, and teams that work extensively with Spark code.

Its governance layer, Unity Catalog, is mature and granular, with fine-grained access controls that remain consistent across workspaces and cloud environments.

Microsoft Fabric stands out when the priority is business intelligence tightly integrated with Power BI. Direct Lake mode removes the need to import data to deliver fast reporting, while governance can build on Microsoft Purview, which many organizations already use.

Governance: an often overlooked factor

Databricks provides more granular, multi-cloud access control through Unity Catalog, including row-level and column-level security that follows the data wherever it is accessed.

Microsoft Fabric takes a more centralized, tenant-based approach to governance, with native Microsoft Purview integration for data lineage and sensitivity labels.

For organizations already invested in the Microsoft ecosystem, this integration can reduce configuration effort. For organizations operating across multiple clouds or dealing with more complex compliance requirements, Unity Catalog’s maturity can offer a meaningful advantage.

What about pricing?

Microsoft Fabric is priced by capacity. You purchase a shared pool of computing power, measured in Capacity Units, that can be used across workloads. This can make monthly costs more predictable (Microsoft Azure, Microsoft Fabric pricing, as of the publication of this article).

Databricks is priced based on actual usage, using Databricks Units (DBUs), in addition to the underlying compute and storage costs.

Fabric’s model tends to work well for stable, predictable workloads. Databricks can be more cost-effective for variable workloads, but it also requires closer cost monitoring to avoid unexpected spending.

The two platforms can work together

Fabric and Databricks both use the open Delta Lake format, which makes using the two platforms together a realistic option.

Many organizations use Databricks for advanced data engineering and machine learning, then make the prepared data available in Fabric for Power BI reporting.

Mirroring Unity Catalog in Fabric also makes it possible to share governed data between the two platforms without duplicating it (Valorem Reply, Databricks vs. Microsoft Fabric comparison, as of the publication of this article).

How to choose

• Your organization already works primarily in the Microsoft ecosystem, including Microsoft 365, Power BI, and Purview: Fabric is a natural fit.
• Your team includes experienced data engineers who work with Spark code every day: Databricks may make better use of their existing expertise.
• Most of your workloads are business intelligence on relatively clean data: Fabric, combined with Power BI Direct Lake, may be more than enough.
• You are planning advanced machine learning initiatives or pursuing a multi-cloud strategy: Databricks has the advantage.

In summary

Neither Fabric nor Databricks is objectively better. The right choice depends on your current technology ecosystem, your team’s expertise, and the types of workloads you need to support.

Our data engineering team can assess these factors with you before recommending the right direction.

Trying to decide between the two platforms for your next project? Talk to one of our experts.