Definitely want Model and DAO classes with any DB specifics abstracted away at their interface. Business logic goes into the service layer above. It's not uncommon to have a service layer level of crud that includes logic to create other required entities or perform complex validations. Service and API layers should always be totally agnostic to data layer. A generic "database proxy" like you described should be solved by your ORM and would live below your DAOs.
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Sounds like the repository pattern would help here.
I’m doing something similar now where I need to store objects “somewhere”. I have a low level Repository interface to handle persistence that can do the basic CRUD (mainly get/set for my use case). It’s primarily backed by redis, but that same interface has been backed by Postgres, vault, and in-memory caches depending on the need/environment. Works amazingly well.
As a bonus we can create a new Repository to migrate data when needed - such as a redis or postgres upgrade, we build a MigratingRedisRepository that takes in 2 RedisRepository and does the necessary logic of reading from the old and writing to the new.
I think you’re on the right track with a mix of 1&2. Abstract out the data store, it will change some time - and you’ll want to control it for tests too. Let services/managers handle state and delegate down for persistence to wherever that may be.