What you’re describing sounds like it fits perfectly into PostGiS. You can have tables and you can normalize your geospatial data. With SQL, and temporary tables, you can build absolutely any analytics.
I worked in a GIS Lab with an ESRI endorsed all Arc stuff textbook author/instructor for a number years. Working on similar projects, for anything remotely complicated, I could implement anything he could do, with some python and PostGIS SQL, usually faster, and instantly reproducible.
ArcGIS is a crutch for people who can’t and aren’t willing to program. This goes for all data manipulation tools that aren’t focused on visualization.
If you have an ETL pipeline, probably best to get GIT involved.
I worked in a GIS Lab with an ESRI endorsed all Arc stuff textbook author/instructor for a number years. Working on similar projects, for anything remotely complicated, I could implement anything he could do, with some python and PostGIS SQL, usually faster, and instantly reproducible.
ArcGIS is a crutch for people who can’t and aren’t willing to program. This goes for all data manipulation tools that aren’t focused on visualization.
If you have an ETL pipeline, probably best to get GIT involved.