All stacks · Cloud platforms
Data Factory, Synapse, Event Hubs, and Microsoft Fabric.
AzureA practical guide to the Azure data platform: when to use Data Factory, what happened to Synapse, and how Microsoft Fabric changes the picture.
AzureA component-by-component migration map from Synapse to Fabric, the T-SQL and workload management gaps that bite, and the order I move things in to keep risk low.
AzureHow to build one Data Factory pipeline that ingests 300 tables instead of 300 pipelines, and how to size integration runtimes so the bill and the SLA both work.
Microsoft FabricOneLake shortcuts are not a copy job, capacity units are shared, and a Power BI refresh can queue a Spark notebook. Fabric is not rebranded Synapse.
Azure runs a huge share of enterprise data platforms, and Microsoft is consolidating its story around Fabric — OneLake, lakehouses, and a SaaS-ified toolchain on top of the ADLS + Data Factory + Databricks stack that most existing platforms are built on.
The tutorials here cover both generations honestly: ADF pipelines that stay maintainable, ADLS Gen2 layouts, Azure Databricks integration, and a clear-eyed view of what Fabric changes, what it renames, and when migrating from Synapse actually pays.
Not dead, but clearly in maintenance mode strategically — Microsoft's investment is in Fabric. Existing Synapse deployments keep working; new greenfield projects should evaluate Fabric or Databricks first.
A SaaS bundle: OneLake (managed Delta storage), lakehouse and warehouse compute items, Data Factory-style pipelines, real-time intelligence, and Power BI, all under one capacity-based pricing model. Think "Microsoft's answer to Databricks + Snowflake + Power BI in one tenant."
If your organization has committed to Fabric capacities, use Fabric pipelines for lake-bound work. Otherwise ADF remains the battle-tested default for enterprise extract-and-load, with far more connectors and years of production hardening.
Databricks for serious Spark engineering, ML, and multi-cloud portability. Fabric for Microsoft-centric analytics teams who live in Power BI and want managed simplicity. Large estates increasingly run Databricks for engineering with Fabric/Power BI as the serving layer.
OneLake is a managed layer over ADLS Gen2 with one logical namespace per tenant, storing tables as Delta. Shortcuts mount existing ADLS (and even S3) locations into OneLake without copying, which is the sane migration path.
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