For most mid-market organisations already on Microsoft 365, we default to Microsoft Fabric — at roughly $5k/month for an F64 capacity, the compute is often already partly covered by existing E5/F5 licensing, and it integrates natively with the Microsoft stack the business already runs on. We move off that default for an existing Databricks estate, ML-heavy workloads, multi-cloud data sharing, or a non-Microsoft shop.
| Feature | Microsoft FabricOur mid-market default | Databricks / SnowflakeSpecialist alternatives |
|---|---|---|
| Typical mid-market cost | ~$5k/month at F64 capacity | Consumption-based — scales with usage, harder to forecast |
| Existing licensing overlap | Capacity often already partly covered by E5/F5 | No overlap with Microsoft licensing |
| Microsoft 365 / Power BI integration | Native — same tenant, same identity | Connector-based, no native tenant integration |
| ML / data science workloads | Improving, but less mature | Databricks: purpose-built, best-in-class for ML |
| Multi-cloud / cross-cloud data sharing | Azure-centric | Snowflake: strong cross-cloud sharing model |
| Non-Microsoft shops | Weaker fit without an Azure/M365 footprint | Cloud-agnostic, no Microsoft dependency |
Pros
Cons
Pros
Cons
Source: Industry market-share estimates, 2026
Source: Industry market-share estimates, 2026
Source: Industry market-share estimates, 2026
Source: Industry market-share estimates, 2026
Source: Industry market-share estimates, 2026
Most mid-market organisations we work with are already Microsoft shops — Microsoft 365, Azure AD, often Power BI in use somewhere already. Fabric's F64 capacity tier runs at roughly $5k/month, and because it's licensed through the same Microsoft agreement as everything else, the capacity cost is frequently already partly absorbed by existing E5 or F5 licensing. Combined with native integration into the identity and BI tools the business already runs, Fabric is the lowest-friction default for a governed data platform — not because it's the most powerful option on every axis, but because it's the one that costs the least to adopt and operate for a Microsoft-centric business.
We move off the default in four situations: the client already has a Databricks estate and switching would mean re-platforming working pipelines for no real gain; the workload is genuinely ML-heavy, where Databricks' notebook and MLOps tooling is more mature; the client needs to share data across multiple clouds or with external partners, where Snowflake's data-sharing model is stronger; or the client isn't a Microsoft shop at all, in which case Fabric's advantage — deep Microsoft integration — simply doesn't apply.
We don't fake a preference. Snowflake remains the market leader by adoption and has the strongest cross-cloud data-sharing story of the three; BigQuery is a strong serverless option for teams already committed to Google Cloud. Neither is a bad choice — they're simply not the lowest-friction default for the Microsoft-centric mid-market clients this recommendation is written for.
Microsoft Fabric: default for Microsoft-centric mid-market teams wanting one platform for data engineering, warehousing, and BI. Databricks: existing Databricks estate, or ML/data-science-heavy workloads where notebook-first tooling matters. Snowflake: multi-cloud or cross-organisation data sharing is a core requirement. BigQuery: teams already committed to Google Cloud who want a serverless warehouse with minimal ops. Redshift: existing AWS-native shops with a mature AWS data estate and no near-term reason to move.
For a Microsoft-centric mid-market business, Fabric is usually the lower-friction default — its F64 capacity costs around $5k/month, that cost is often partly covered by existing E5/F5 licensing, and it integrates natively with Microsoft 365 and Power BI. Databricks or Snowflake are better fits for ML-heavy workloads or multi-cloud data sharing.
Fabric's F64 tier is a predictable ~$5k/month, and mid-market Microsoft shops often already have partial capacity coverage through E5/F5 licensing. Databricks and Snowflake are consumption-priced, which can be cheaper or more expensive depending on workload — but is harder to forecast upfront.
Choose Databricks when you already run a Databricks estate, or when the workload is genuinely ML-heavy — Databricks' notebook and MLOps tooling is more mature than Fabric's equivalent today.
Choose Snowflake when you need strong cross-cloud or cross-organisation data sharing, or when the business isn't a Microsoft shop and gets no benefit from Fabric's native Microsoft 365 integration.
For most mid-market organisations already on Microsoft 365, we default to Microsoft Fabric — at roughly $5k/month for an F64 capacity, the compute is often already partly covered by existing E5/F5 licensing, and it integrates natively with the Microsoft stack the business already runs on. We move off that default for an existing Databricks estate, ML-heavy workloads, multi-cloud data sharing, or a non-Microsoft shop.
