Unified Data Analytics Experience in Azure Synapse Analytics

Introduction  

Azure Synapse Analytics launched in 2019 to solve the problem of data integration, enterprise data warehousing, and big data analytics being spread across separate tools. It brought Azure Data Factory pipelines, Power BI, and Data Lake Storage together into a single workspace. For several years, it was the default recommendation for teams building an analytics platform on Azure.

That recommendation has changed. Microsoft’s active development has shifted to Microsoft Fabric, a newer SaaS-based analytics platform, while Synapse continues to run in production and receive security patches. 

What Is the Unified Data Analytics Experience in Azure Synapse Analytics?

Synapse brings data integration, warehousing, and big data analytics into a single workspace. It helps data engineers, analysts, and data scientists work in the same environment rather than stitching tools together.

• Data integration: Synapse Pipelines connect more than 90 data sources for batch and real-time ingestion, inside the same workspace used for warehousing and analytics.
• Enterprise data warehousing: Dedicated and serverless SQL pools handle structured reporting workloads without a separate warehouse product.
• Big data analytics: Spark pools query structured, semi-structured, and unstructured data directly against Data Lake Storage.

None of this has stopped working. It is simply no longer the newest or most actively developed way to do it, which matters once you start planning past this year.  

How Is Azure Synapse Analytics Architected?

Synapse Studio remains the workspace for building pipelines, running SQL and Spark, and managing jobs. Underneath it, workloads map to Dedicated SQL Pools, Serverless SQL Pools, and Spark pools, each drawing on its own storage in Azure Data Lake Storage Gen2. This detail matters once you compare Synapse to Fabric, where storage works differently.

One correction worth making for anyone still working from older notes: “Azure SQL Data Warehouse” has not been the product name for years. Synapse dedicated SQL pools replaced it, and Synapse itself is the umbrella product rather than a feature bolted onto a warehouse.

Azure Synapse Analytics vs. Microsoft Fabric: How Do They Compare?

Synapse and Fabric differ most in their delivery models, storage architectures, and where Microsoft is investing. The table below breaks it down. Fabric bundles data integration, engineering, warehousing, real-time intelligence, and Power BI into a single SaaS workspace on a shared storage layer, OneLake, removing the copy steps that Synapse requires between workloads. It has passed a $2 billion annual revenue run rate and is growing roughly 60% year over year, with nearly all of Microsoft’s new analytics capability landing there first.

Synapse still wins in granular infrastructure control and a couple of Spark capabilities, such as GPU-accelerated pools. Fabric wins on almost everything else, especially where AI and unified governance matter.

Should You Migrate Before Year-End Close, or Wait?

It depends on the workload. You can start anything new on Fabric, and let stable, GPU-dependent Synapse jobs keep running through year-end. Most organizations are closing out this year’s numbers and building next year’s technology budget at the same time, which makes this the right moment to decide deliberately rather than react under pressure.

• New workloads: build them on Fabric. There is little reason to invest in new Synapse pipelines or warehouses when Microsoft’s active development is elsewhere.
• GPU-dependent Spark jobs: these can reasonably stay on Synapse until Fabric closes the gap.
• Team bandwidth this quarter: a rushed migration during year-end close is a bad idea. Budget it into 2027 and execute in a controlled window.
• Cost predictability: Fabric’s capacity-based pricing simplifies forecasting compared with Synapse’s per-resource billing.

How Does Migration Actually Work?

Microsoft offers free, guided migration assistants for pipelines, Spark workloads, and data warehousing that automatically convert existing artifacts and validate results before anything goes live, so migration does not require rebuilding from scratch.

OBOS BBL, a large Nordic housing cooperative, migrated more than 600 notebooks and pipelines this way and reported 30% faster processing and 20% lower operational costs, running old and new environments in parallel until the numbers matched.

Conclusion

You can keep what already works on Synapse, and build anything new on Microsoft Fabric. Synapse still handles data integration, warehousing, and big data analytics well. What has changed is where Microsoft is putting its money: it is now in Fabric.

Deciding exactly what to move, what to leave alone, and when to do so takes more than a comparison table. AlphaBOLD’s data engineering team has guided organizations through this exact Synapse-to-Fabric decision, and can assess your environment before your 2027 budget is locked in.

Request a consultation, and we will show you what to move, what to keep, and the order in which to move them.

FAQs

Is Microsoft discontinuing Azure Synapse Analytics?

No end-of-life date has been announced. Synapse remains supported with security patches, though new feature development is focused on Fabric.

Can Synapse and Fabric run side by side?

Yes. Many organizations run both during a transition and migrate workloads gradually using Fabric’s migration assistants.

Does moving to Fabric mean rebuilding everything?

Not necessarily. The migration assistants preserve existing logic and automatically convert artifacts, with validation before cutover.

Is Microsoft Fabric more expensive than Azure Synapse Analytics?

It depends on the workload. Fabric’s capacity-based pricing can lower costs for teams over-provisioning Synapse resources, but steady-state, high-volume workloads should be modeled against both pricing structures before deciding.

Should a new project start on Synapse or Fabric in 2026?

Fabric. Unless there is a specific need for Synapse’s PaaS-level control or GPU Spark pools, new analytics projects belong on the platform Microsoft is actively developing.