The macOS app is a helper tool for me to process data and manage its representation in CloudKit. But it’s currently stateless. It decodes JSON and writes directly to a public database – so I can reset the CloudKit developer environment as needed and quickly stand it back up with schemas and records.

But as I started modeling a new metadata type that isn’t represented in the source JSON, I realized the Mac app needs a data store of it’s own.

Maintaining the source schemas from each data source as its own record type has been a good choice. Now I have a small catalog of data from 3 places loaded into CloudKit. And a simple iOS app with a picker between 3 SwiftUI views – each tuned to its source. So each feels the same.

Next I’ll model some common metadata concepts from across the 3 schemas as new CloudKit record types. I’ll expand the macOS writer app to run queries against the existing data catalog, create new CloudKit metadata records and build an object graph between content and tags using CKRecord.Reference. So the iOS reader can query against these common metadata records, and get back references to records from all 3 sources.

I went down the path of trying to define a source agnostic schema, thinking I would transform all the incoming data to a common record type in the macOS app before loading it into CloudKit.

But this adds some pressure to get the data normalization “right” on ingest. Now I’m exploring an alternative approach, where I maintain a 1:1 relationship between data source schemas and CloudKit record types.