It is always good to see new approaches to testing but I don't see how this one is going to work. I've worked at multiple database companies. Diff'ing data is one of the weakest and most cumbersome ways to verify correctness.
Diffs are relatively slow, when they fail you get a blizzard of errors, and the oracles (i.e. the "good" output) have to be updated constantly as the product changes. Plus I don't see how this helps with schema migration or performance issues, which are major problems in data management. And don't get me started on handling things like dates, which change constantly, hence break diffs.
If you really care about correctness it's better to use approaches like having focused test cases that check specific predicates on data. They can run blindingly fast and give you actionable data about regressions. They're also a pain to code but are most productive in the long run.
Diffs are relatively slow, when they fail you get a blizzard of errors, and the oracles (i.e. the "good" output) have to be updated constantly as the product changes. Plus I don't see how this helps with schema migration or performance issues, which are major problems in data management. And don't get me started on handling things like dates, which change constantly, hence break diffs.
If you really care about correctness it's better to use approaches like having focused test cases that check specific predicates on data. They can run blindingly fast and give you actionable data about regressions. They're also a pain to code but are most productive in the long run.