This is the question I get most often in client engagements now. "We're starting a new data platform project. Should we use ADF or Synapse Pipelines?" I've given versions of this answer probably thirty times in the past year. Here's the complete version.
The Short Answer
Use whichever surface your team will actually work in. If that doesn't help you decide, read on.
What They Actually Are
ADF is a standalone data integration service. You access it through ADF Studio (adf.azure.com), manage it independently, and it integrates with everything in Azure but isn't embedded in any particular workspace. It's designed to be shared -- a central ADF instance serving multiple consumers across the organization.
Synapse Pipelines is the orchestration capability inside Azure Synapse Analytics. You access it through Synapse Studio, and it lives in the same workspace as your Synapse SQL pools, Synapse Spark pools, and your data lake. It's designed for analytical workflows where the orchestration is co-located with the compute it's orchestrating.
The technical capability of both is nearly identical -- same connector library, same activity types, same Data Flow engine, same trigger model. The differentiation is organizational and workflow-based, not feature-based.
When ADF Is the Right Choice
You have a standalone data integration team. The team's job is to build pipelines that move data from sources into a data platform that other teams consume. They don't live in a Synapse workspace -- they live in ADF Studio, Azure DevOps, and whatever monitoring tools they've wired up. ADF is their product.
You have existing ADF investment. Production pipelines, established CI/CD patterns, institutional knowledge of the ADF Studio workflow. Migrating to Synapse Pipelines provides no technical benefit and carries real migration risk.
You want centralized governance of data integration. One ADF instance as the integration layer for the organization, with clear ownership, access controls per pipeline, and a single place to find and audit all data movement.
You're building pipelines that serve multiple downstream consumers. Pipelines that feed the data warehouse, the ML platform, and the reporting layer. These are organizational assets, not just part of one analytical workflow.
When Synapse Pipelines Is the Right Choice
You're building a Synapse Analytics workspace. Your team is going to live in Synapse Studio. You've got Synapse SQL pools and/or Synapse Spark pools as your primary compute. Co-locating pipeline authoring in the same workspace as your compute reduces context switching.
The pipeline is tightly coupled to a specific analytical workflow. ETL that loads a Synapse SQL pool dedicated to one department, orchestrated alongside Synapse Spark notebooks that the same team writes and runs.
You're starting fresh with no existing ADF investment. No migration cost, no retraining. If Synapse is where you want to end up, build there from day one.
The One Thing You Should Not Do
Migrate a working ADF deployment to Synapse Pipelines because Synapse is newer. There is no technical benefit, only migration cost. The pipeline JSON is nearly identical, but you're still rebuilding linked services, reconfiguring integration runtimes, rewiring CI/CD, and retraining the team on a slightly different studio experience for zero functional gain.
I've been asked to scope this migration twice this year. Both times I told the client the same thing: don't. If something is broken about your current ADF deployment, fix the broken thing. If everything is working, leave it alone.
The Skills Question
ADF and Synapse Pipelines skills transfer 1:1. An engineer who knows ADF can work in Synapse Pipelines in an hour. The JSON schemas are nearly identical. If you're thinking about this from a hiring and team skills perspective, it doesn't matter which one you pick -- an "ADF experience" requirement and a "Synapse Pipelines experience" requirement are interchangeable.
The Long View
My expectation is that these products converge over the next few years -- probably under the Microsoft Fabric umbrella when that's fully public. Both ADF and Synapse Pipelines skills will transfer to whatever comes next. The investment you're making in patterns, parameterization, CI/CD, and monitoring applies regardless of which surface you're building on today.
If you're still not sure which is right for your specific situation, tell me more about your team and architecture. I'm here to help.