I worked in the data federation space for a number of years (it's actually quite an old term, I worked in it back in 2013, around the time there was an early wa

I worked in the data federation space for a number of years (it's actually quite an old term, I worked in it back in 2013, around the time there was an early wave of activity around this and the concept of a "data fabric"). When I saw GraphQL come out, I knew that what you are saying would happen. In the data federation tool I worked in, SQL was the interface abstraction to join across heterogenous platforms (think of things like Presto/Trino or Dremio). GraphQL as an interface requires the same underlying infrastructure as that data federation tool I worked on in terms of query analysis, parsing, planning, optimization, execution, etc. Those are "hard problems" due to lack of standardized interfaces, access patterns, direct data access, I/O, network bandwidth and infra related latency, costs, compatibility, data types, etc. These problems are distributed system problems coupled with often incompatible interface layers (e.g., even if you are using multiple SQL databases with GraphQL, you run into the same). If your scale is such that you can build GraphQL on a handful of systems and for a handful of use cases, great! If you have to go to a certain larger scale, you're back into federation territory (which in the app layer might also be called API composition). One potential option - when you reach the point where you need complex GraphQL query coordination, more than seems to make sense to implement, pair it with a data federation tool such as Presto/Trino, Dremio, Denodo, or research approaches such as caching/materialized views (engines like that are becoming decoupled from databases, such as Materialize.io) - and let those engines do the hard work. In that case your work becomes more like GraphQL -> SQL or API -> a data federation, caching or materialization platform. CQRS and event sourcing plays a role here too. Consider also, the possibility that if you are willing to accept a bit of delay in aggregated results from multiple systems, doing those compositions or aggregations in the data platform layer, and simple feeding those to the GraphQL interface. That could even be done in a single database/data platform if you really wanted without too much fancy federation tech. Federation is powerful but complex. It seems like a fun hard problem, but for many tech teams, it can be a complexity and time suck. My recommendation would be try to avoid building that if you can.