If you change your schema once every 2-3 days, something wrong with whomever leading the software project. That's like writing a software with zero planning or lack of knowledge for the problem domain.
I don't care if it is a startup or not. Come up with a very simple idea, draw the models in ER diagram, implement that stuff.
It's very hard to imagine that tomorrow suddenly all relationships need to be changed. Even if that is the case, scrap your Repository/Entity model and start from the beginning.
Nothing can help you much if the fundamentals are wrong.
Everything else in a software project changes frequently, especially during the early days. "Fundamentals" don't help you know more ahead of time and it's really nice to be able to quickly adjust when you come across something you hadn't anticipated.
I tried building a small side project with Postgres about 8 months ago (after not really doing rdbms stuff for 18 months before) and was amazed at how inflexible it felt, and how much frustration used to seem normal.
I write up a schema, send to everyone else on the team, get feedback. If users are invovled get it from them too....
take in all the feedback, write up a new draft, wash, rinse, repeat until running out of shampoo (i.e. feedback).....
Once things are pretty stable, do a prototype, address any oversights, do the real thing.
As a startup, change of minds is pretty normal to the point that it's far more better to have the tools to quickly implement it rather than plan/document it well. The only documentation is the general gist behind the database.
If it prototypes well, then further refine it with ER diagrams for future maintenance.
Why is planning everything without validation better than above?
Disagree here. Figure an hour of planning saves 10 hrs dev time and 100 hrs bugfixing.
That doesn't mean spending months planning. It does mean doing your best to plan over a few days, then prototype, review, and start implementing. If things change, you now have a clearer idea of the issues and can better address them.
The worst thing you can do is go into development both blind and without important tools you need to make sure that requirements are met--- tools like check constraints, referential integrity, and the like.
Maintenance takes up about 50% of all IT budget [1]. Most individual pieces of software will spend 2-6 times (considering the average life cycle of an in production software product to be 2-4 years) more money on being maintained than being developed.
Data migration is a massive problem for any organization with data sets at any scale. RDBMS, in general, has gotten in the way of those migrations. People aren't looking at NoSQL just because they cannot sit still but instead are looking to find a better experience with handling data.
I'm not sure if NoSQL is the right answer to that but let's give it a chance and see what happens when people are migrating MongoDB data in 3-4 years.
Integration issues are best handled with good API's. Migration issues are a bigger issue but one thing that good use of RDBMS's give you is the ability to ensure your migrated data is meaningful. Not sure you can do that with KVM-type stores.
I don't care if it is a startup or not. Come up with a very simple idea, draw the models in ER diagram, implement that stuff.
It's very hard to imagine that tomorrow suddenly all relationships need to be changed. Even if that is the case, scrap your Repository/Entity model and start from the beginning.
Nothing can help you much if the fundamentals are wrong.