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.
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.
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