Microsoft Fabric vs. Azure Synapse: What's the difference?

Companies looking at data architecture and business intelligence solutions in the Microsoft ecosystem will sooner or later come up against the same question: Microsoft Fabric vs Azure Synapse Analytics - which is right for us? Both platforms promise scalable data analysis. And yet they differ fundamentally in their philosophy, architecture and area of application.

In this article, we explain the key differences between Microsoft Fabric and Azure Synapse Analytics, show which solution is suitable for whom - and how prodot can help you make the right decision.

What is Microsoft Fabric?

Microsoft Fabric is a cloud-based analytics platform that is provided as Software-as-a-Service (SaaS). It combines under one roof:

• Data engineering: pipelines, Spark-based transformations
• Data warehousing: SQL-based warehouse with high performance
• Data science: ML experiments and model training
• Real-time analytics: streaming data with KQL (Kusto Query Language)
• Business intelligence: Power BI as a native reporting layer
• Data Factory: Data movement and orchestration
• Synapse SQL: Dedicated and serverless SQL pools for different workloads
• Synapse Spark: Apache Spark for big data processing and ML
• Synapse Pipelines: Orchestration based on Azure Data Factory
• Synapse Link: Near-real-time integration with Cosmos DB, Dataverse and others.
• Azure Machine Learning: External connection for advanced ML workflows

At the heart of Fabric is OneLake - a central, unified data lake that is accessed by all components of the platform. Files are stored in open formats such as Delta Lake and Apache Iceberg, which minimizes vendor lock-in and maximizes interoperability.

Particularly relevant for enterprise use: Microsoft Copilot is deeply integrated into Fabric and enables AI-supported analyses, code generation and natural language data queries directly in the platform.

What is Azure Synapse Analytics?

Generally available since 2020, Azure Synapse Analytics is positioned as a Platform-as-a-Service (PaaS) solution for enterprise data integration and analytics. Synapse brings the following core capabilities:

• Synapse SQL: Dedicated and serverless SQL pools for different workloads
• Synapse Spark: Apache Spark for big data processing and ML
• Synapse Pipelines: Orchestration based on Azure Data Factory
• Synapse Link: Near-real-time integration with Cosmos DB, Dataverse and others.
• Azure Machine Learning: External connection for advanced ML workflows

Synapse's data storage is flexibly configurable - typically Azure Data Lake Storage Gen2 (ADLS Gen2). The platform is primarily aimed at experienced data engineers and architects who require full control over their infrastructure.

Microsoft Fabric vs. Azure Synapse: A direct comparison

The 5 most important differences in detail

1. SaaS vs. PaaS - the fundamental architectural philosophy

Microsoft Fabric is designed as a fully managed SaaS service. This means that Microsoft takes care of infrastructure, updates and capacity management. For companies without a dedicated cloud infrastructure team, this is a decisive advantage - the platform is ready to use immediately, without time-consuming configuration.

Azure Synapse, on the other hand, is a PaaS offering: companies have full control over resources, scaling and configuration. This enables highly granular cost optimization and customization, but requires corresponding technical expertise and more operational effort.

2 OneLake vs. ADLS Gen2 - data storage and storage architecture

One of the most differentiating features is how data storage is handled. Fabric introduces OneLake - a single, logically unified data lake for the entire organization. Every department, every team uses the same data storage, which structurally dissolves data silos.

Azure Synapse is more flexible in terms of storage configuration, but also more complex: companies have to configure and manage their own ADLS Gen2 account. In heterogeneous environments, this can be an advantage - in homogeneous environments, it is often just additional complexity.

3 AI and Copilot integration

Microsoft Fabric is built from the ground up for the AI age. Microsoft Copilot is natively embedded and supports users in querying data in natural language, generating SQL code or describing data flows. This significantly lowers the barrier to entry for business users.

In Azure Synapse, AI is primarily accessible via external services such as Azure Machine Learning or Azure OpenAI Service. Integration is possible, but not seamless - and requires separate configuration and authorization management.

4 User-friendliness and target group

Fabric is deliberately aimed at a broad target group: from data scientists to business analysts. The uniform interface, the workspace concept and low-code functions make it much easier to get started.

Azure Synapse requires more prior technical knowledge. Its strengths lie in its flexibility and depth - this is an advantage for specialized data teams that require tailor-made solutions.

5 Licensing and cost model

Fabric uses a capacity-based model (so-called F-SKUs). Companies purchase or book Fabric Capacity - all services on the platform are billed using this. This simplifies cost planning and control considerably.

Azure Synapse bills based on resources: Dedicated SQL pools via DWUs, Spark via vCores, pipelines via activity executions. For experienced teams, this offers optimization potential - for others, it quickly leads to unexpected costs.

Fabric vs. Azure Synapse: When should companies choose which platform?

Microsoft Fabric is the better choice when...

• ... a centralized, unified data and analytics ecosystem is to be established
• ... close Power BI integration is desired
• ... the use of AI functions (Copilot) in the data area is planned
• ... low infrastructure complexity and fast time-to-value are important
• ... teams from different departments need to access data together
• ... the company relies on a modern, future-oriented Microsoft stack

Azure Synapse is the better choice if...

• ... highly complex, customized data architectures are required
• ... existing Azure infrastructure (ADLS, ADF, Azure ML) is already in place
• ... granular control over compute resources and costs is required
• ... there are specific compliance or data localization requirements
• ... the team has in-depth technical expertise in the Azure world
• ... Synapse Link is required for Cosmos DB or Dataverse scenarios

Can Microsoft Fabric and Azure Synapse be used at the same time?

Yes - and in practice this is a realistic transition phase for many companies. Existing Synapse workloads can be gradually migrated to Fabric, while new projects can be set up on Fabric from the outset. Microsoft provides migration guides and tools to facilitate this transition.

A structured migration strategy is crucial: Which workloads can be migrated immediately? Where are there technical or functional dependencies? Where will duplicate costs arise in the short term? These questions should be clarified before the start.

Conclusion: Microsoft Fabric as the strategic platform of the future

Microsoft Fabric is not just an upgrade of Azure Synapse - it is a paradigm shift in the way companies work with data. The unification of data storage, analytics, AI and reporting in a single SaaS platform eliminates structural silos and significantly reduces the total cost of ownership.

Azure Synapse remains relevant for technically demanding scenarios and existing architectures - but should be seen as part of a fabric strategy in the medium term, not as an alternative.

For companies investing in their data strategy today, Microsoft Fabric is the future-proof choice.

Would you like to know whether Microsoft Fabric or Azure Synapse Analytics is the right choice for your data strategy - and how to get started? Get in touch with us. We'll take a look together.