Pydantic is using classes and typehinting. The new dataclasses style. Currently Maat doens't have a parser for dataclasses, it could come in the future. Pydantic works great with typehinting.
If only for conciseness, readability and speed, I'd take Pydantic over any day. Being able to express 80% of type checking using Python native type hints + dataclasses is just so intuitive!
And it's getting some wide adoption, for instance FastAPI which uses it for request validations.
Mmmh interesting requirement! Indeed, defining very nested structure with Pydantic is one of its weaknesses.
And of course I agree 100% about tradoffs in engineering. However I usually advise against using 2 dependencies doing mainly the same thing if possible within the same project.
Maat was created before dataclasses existed. For validation Maat offers the same. But it also allows for some really neat features such as validation on encrypted data. https://github.com/Attumm/Maat/blob/main/tests/test_validati...
Since validation is written as dictionaries its possible to store the validations in caching db such as Redis.
And since its simple its easy to extend for anyone use case. And there are no other dependencies.
Benchmarks of pydantic has Maat around twice as Pydantic.