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Compare Microsoft technologies
Pick up to four. The comparison starts by saying whether they compete, work together or sit in different layers, then lines up their verified facts. It never names a universal winner.
How they relate
Microsoft Fabric and Azure Databricks work together.
From the published profiles: one can integrate the other.
Microsoft Fabric and Azure Synapse Analytics can be compared as alternatives for some goals.
From the published profiles: documented as alternative approaches.
Azure Databricks and Azure Synapse Analytics can be compared as alternatives for some goals.
Based on their architecture layers and types; no direct relationship is documented in the profiles.
Side by side
| Fact | Microsoft Fabric | Azure Databricks | Azure Synapse Analytics |
|---|---|---|---|
| Type | Cloud application | Cloud service | Cloud service |
| Layers | Data & analytics, AI models & platform | Data & analytics, AI models & platform | Data & analytics |
| What it is | Microsoft Fabric is Microsoft's SaaS analytics platform. Data integration, Spark data engineering, warehousing, real-time analytics, data science, operational databases and Power BI share one lake (OneLake) and one capacity-based license, so teams do not have to wire separate Azure services together. | Azure Databricks runs the Databricks Data + AI Platform on Azure: an Apache Spark lakehouse with Delta Lake tables, Unity Catalog governance, SQL warehouses, MLflow and model serving. It suits teams that need Spark-scale data engineering, machine learning and AI agents over their own cloud storage. | Azure Synapse Analytics is Azure's earlier analytics service, combining dedicated and serverless SQL pools, Apache Spark pools and Data Factory-style pipelines in one workspace. It is still supported, but Microsoft's guidance is to prefer Microsoft Fabric for new investments, and it provides migration tools. |
| Who needs it | Organizations that want one governed analytics estate instead of separate ingestion, lake, warehouse and BI services, especially those already on Power BI or Microsoft 365. Microsoft's architecture guidance positions Fabric for teams whose machine learning is part of a wider analytics workflow and who want a managed SaaS service with little infrastructure to run. Power BI Premium P SKU customers are also directed to Fabric F SKUs as the P SKUs retire. | Data engineering, data science and ML teams that process very large datasets on Spark, want one lakehouse for engineering, feature work and model development, and need production MLOps with managed serving endpoints. Microsoft's architecture guide also points to Azure Databricks when governance of data, features, models and functions in Unity Catalog is a requirement. | Organizations that already run Synapse dedicated SQL pools, Synapse Spark or Synapse pipelines in production and must keep them running while they plan their next step. Microsoft also lists cases where Synapse Spark still fits better than Fabric Spark: GPU-accelerated pools, an external Hive Metastore, JDBC connections and .NET for Spark (C#). |
| What it is not | Fabric is not a renamed Power BI: Power BI is one Fabric workload, and Power BI Pro or Premium Per User licenses do not provision Fabric capacity for lakehouses, warehouses or notebooks. It is not an Azure PaaS service deployed into your subscription; it runs as SaaS in your Microsoft Entra tenant, with capacity bought through Azure. Microsoft says it is not a replacement for a dedicated machine learning platform when you need deep learning at scale, full MLOps or fine-grained compute control. Fabric Spark also lacks GPU pools, an external Hive Metastore and .NET for Spark. | Azure Databricks is not a database or a storage system; it runs analytics over cloud storage. It is not Microsoft Fabric: Fabric is SaaS licensed by capacity, while Databricks bills Databricks Units, plus Azure VMs, storage and networking for classic compute. Microsoft says it is not the right fit when a team does not need Spark-scale processing, or when a scenario only calls AI models through APIs, where Foundry Tools or Microsoft Foundry are more direct. | Synapse is not where Microsoft wants new analytics projects to start: its Azure Architecture Center says to prefer Microsoft Fabric for new investments. Synapse is also not the same product as Fabric Data Warehouse or Fabric Spark, even though Microsoft documents migration paths between them. Synapse Data Explorer is no longer an option; Microsoft set its retirement for 7 Oct 2025, said workloads would be deleted, and recommends Eventhouse in Fabric instead. |
| Prerequisites |
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| Runs on | Microsoft-hosted SaaS in the Fabric portal, Capacity purchased through Azure or a Cloud Solution Provider, Cross-tenant sharing through OneLake external data sharing | Azure regions (serverless compute in the Azure Databricks account), Classic compute in your Azure subscription and virtual network | Azure regions as a PaaS workspace in your subscription |
| Availability and licensing | Generally available. Capacity is sold as F SKUs (F2 to F8192) through Azure or a Cloud Solution Provider, billed per second with a one-minute minimum and optional yearly reservations; prices vary by region. A 60-day trial gives F64-equivalent capacity. Fabric IQ is in preview, and at Build 2026 (June 2026) Microsoft announced GPU-accelerated query acceleration for Fabric Data Warehouse as an early access preview and the Rayfin SDK as a preview. Fabric is not yet available in sovereign clouds (checked 26 Oct 2026). | Generally available. Billing is usage based: Databricks Units (DBUs), a normalized hourly unit of processing capability billed per second, plus Azure VM, storage and networking costs for classic compute. One- or three-year pre-purchase plans of Databricks commit units discount DBU usage only. Microsoft's Azure product page shows no list prices for Azure Databricks (checked 26 Oct 2026). | Available and supported; the Synapse overview page carries no retirement notice for the service as a whole (checked 26 Oct 2026). Microsoft's Azure Architecture Center (Learn date 30 Jul 2026) says to prefer Microsoft Fabric for new investments. Synapse Data Explorer (preview) was set to retire on 7 Oct 2025, with its workloads deleted. Microsoft's Cloud Migration Factory program offers selected customers hands-on migration help to Fabric at no cost for 6 to 8 weeks. |
| When something simpler is enough | If a small team only needs dashboards over a few sources, Power BI Pro or Premium Per User avoids paying for a capacity. If your team already runs a Spark lakehouse on Azure Databricks with Unity Catalog, or needs GPU training and production MLOps, Microsoft's guidance points to Azure Databricks or Azure Machine Learning rather than moving everything to Fabric. A single operational database with built-in reporting does not need a lakehouse at all. | If your analytics are mainly BI on moderate data volumes and your team prefers SaaS without cluster settings, Microsoft Fabric or Power BI alone may be enough. If you only call hosted AI models through an API, Microsoft points to Foundry Tools or Microsoft Foundry. Microsoft also notes that non-Spark machine learning can be more straightforward in Azure Machine Learning. | For a new analytics project, start with Microsoft Fabric, which Microsoft recommends for new investments, or with Azure Databricks if you need lakehouse-scale Spark and Unity Catalog. For modest reporting needs, Power BI alone may be enough. Keep Synapse where it already runs well, especially where its specific features (GPU Spark pools, external Hive Metastore, .NET for Spark) are still required. |
| Last reviewed | 26 Oct 2026 | 26 Oct 2026 | 26 Oct 2026 |
| Official resources | Product page (opens in a new tab)Documentation (opens in a new tab) | Product page (opens in a new tab)Documentation (opens in a new tab) | Product page (opens in a new tab)Documentation (opens in a new tab) |
Each value comes from the technology's profile, where every statement links to its source. Pricing, benchmark and compatibility claims are not shown unless a profile documents them.
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