In the world of Microsoft’s modern data ecosystem, two names keep coming up in conversation, Azure Synapse Analytics and Microsoft Fabric. They’re both high-powered platforms, both help organisations manage and analyse data, and both promise to simplify how you work with information. On the surface, it’s easy to assume they’re interchangeable. In reality, though, they have different strengths and serve different purposes.
This distinction matters. Choosing one over the other, or even deciding to run both, shouldn’t be a snap judgement. The right decision depends on your organisation’s data maturity, existing technology stack, and future ambitions. We’ve seen businesses rush into one platform without properly evaluating the fit, only to face unexpected rebuilds, spiralling costs, or duplicated effort.
So, what sets them apart, where do they overlap, and how should you decide?
Azure Synapse Analytics in Focus
Azure Synapse Analytics is Microsoft’s enterprise-scale analytics and data warehousing platform. It’s designed for organisations with vast datasets and complex analytical requirements.
At its core, Synapse combines:
- Dedicated and serverless SQL pools for querying data with high performance.
- Integration with Apache Spark for big data analytics and machine learning workloads.
- Native support for Azure Data Lake to store and manage massive amounts of structured and unstructured data, long with seamless integration with Azure Data Factory for orchestrating ETL and ELT pipelines.
Because of this, Synapse tends to shine in enterprises that already have an established Azure footprint and strong in-house data engineering expertise. Its consumption-based pricing model can be cost-effective for fluctuating workloads, but it also means you need to actively monitor usage to prevent surprises.
Microsoft Fabric’s Broader Approach
Microsoft Fabric is an end-to-end, fully managed SaaS data platform that brings together ingestion, transformation, storage, governance, and reporting. It’s designed to give technical teams, analysts, and business users a single, unified environment to work in.
Key capabilities include:
- OneLake – a centralised storage layer for all workloads, ensuring everyone works from the same source of truth.
- DirectLake – allowing Power BI to connect directly to data without time-consuming imports.
- Lakehouse architecture – combining the flexibility of a data lake with the reliability and structure of a data warehouse.
- Built-in governance, compliance, and security.
Where Synapse focuses on raw processing power, Fabric aims to make the entire analytics workflow simpler, faster, and more collaborative.
Where They Differ, and Where They Overlap
The main difference lies in scope. Synapse is about high-performance data warehousing and querying, while Fabric is about managing the entire analytics lifecycle in one place.
That said, they’re not mutually exclusive. We’ve worked with organisations that use Synapse for heavy-duty data processing and Fabric for governance, self-service analytics, and reporting. This hybrid model can work well, provided the two are set up to complement each other rather than duplicate work.
Key Differences
| Aspect | Azure Synapse Analytics | Microsoft Fabric |
|---|---|---|
| Core Purpose | Enterprise data warehousing and analytics platform, optimised for large-scale SQL workloads | End-to-end SaaS data platform covering ingestion, transformation, storage, governance, and visualisation |
| Architecture | Dedicated and serverless SQL pools, Spark integration, Azure Data Lake support | OneLake unified storage, DirectLake for instant Power BI access, Lakehouse architecture |
| Integration with Power BI | Connected but separate, requiring setup and optimisation | Fully integrated, Power BI is built into the platform as the default visualisation layer |
| Governance & Security | Relies on Azure Purview and other Azure services | Governance, compliance, and security are built directly into the platform |
| Pricing Model | Consumption-based, pay for compute and storage separately | Per-user subscription pricing with platform features included |
| Scalability | Highly scalable for analytical workloads | Scales across the entire analytics lifecycle from raw data to dashboards |
Choosing the Right Fit
When deciding between the two, consider:
- Data volumes and complexity – Are you running massive, complex queries? Synapse might be the better fit.
- Team skills – Do you have deep Azure and SQL expertise in-house?
- End-to-end needs – Do you want one platform for everything from ingestion to reporting?
It’s not just about features, it’s about aligning the platform with your business priorities. For more on how a strong data strategy supports better business outcomes, read our blog: Why Data-Driven Decision-Making is Important.
When Fabric is a Best Fit
- You want a single, unified platform that covers ingestion, transformation, storage, governance, and visualisation.
- Business and technical teams both need access to the same, trusted datasets.
- You want to simplify toolsets and reduce the complexity of managing multiple systems.
- Governance, compliance, and data security are high priorities.
When Synapse is a Best Fit
- You handle very large, complex datasets that require high-performance SQL querying.
- Your team has strong Azure data engineering expertise.
- You already have well-established ETL or ELT processes and just need the analytical horsepower.
- You want precise, granular control over performance and cost through a consumption-based model.
FAQs
- Is Microsoft Fabric replacing Azure Synapse Analytics?
No. Fabric is a new platform that includes features overlapping with Synapse, but it does not replace it. Synapse remains a powerful option for high-performance data warehousing and analytics, while Fabric focuses on providing an end-to-end SaaS data experience. - Can Azure Synapse Analytics and Microsoft Fabric work together?
Yes. Many organisations combine Synapse’s analytical power with Fabric’s governance, storage, and self-service analytics to create a hybrid solution that leverages the strengths of both platforms. - Which is better for large datasets, Fabric or Synapse?
For extremely large, complex datasets that require high-performance querying, Synapse is often the better fit. Fabric can handle large volumes too, but its main advantage is in providing a single, unified environment for the entire analytics lifecycle. - What skills are needed for Synapse and Fabric?
Synapse typically requires strong SQL, Azure data engineering, and big data expertise. Fabric is more user-friendly but benefits from knowledge of data modelling, governance, and analytics tools like Power BI. - Is Azure Synapse still relevant in 2025?
Absolutely. Despite the release of Microsoft Fabric, Synapse remains highly relevant for enterprise-scale analytics and will continue to be a core component of many Azure-based data strategies.
The AGER BI Approach
At AGER BI, we help clients navigate this decision by mapping their current environment, clarifying where they want to be, and designing the most efficient path forward. Sometimes that means focusing on one platform, sometimes it means a carefully planned hybrid.
If you’re evaluating Azure Synapse Analytics vs Microsoft Fabric, don’t leave it to guesswork. Book a free consultation and we’ll help you choose with confidence.
