Yeah, I use it at a financial services client. A previous architect chose it because it was a pet project of his (he contributed to Delombok).
The premise is fine...I have no problem with it. But the default generation of @EqualsAndHashcode literally pulls in the WORLD to generate the output.
The real world scenario we had was this. Lots of POJOs were created, many were simply but a non-trivial number were NOT. Those POJOs could have dozens and dozens of fields. And if you have a key abstraction with say, 86 fields, things get interesting.
Suppose you don't use @EqualsAndHashCode on one of these POJOS with lots of fields, ALL 86 fields are included in the default equals and hashCode methods. They didn't realize this, or didn't care, and as a result, had some serious performance issues because trying to run hashCode on insert to a map when you're hashing 86 fields together might actually take some time inserting 100,000 records... ugh
So in short, it's OK and useful, but you have to understand the side effects of everything to know if it's the right thing for you.
SIDE NOTE: A POJO with 86 fields can be common in financial services when you are representing various kinds of financial trades where gazillions of things are tracked on them...interest rates of note, ratings, security characteristics, etc. That in and of itself isn't necessarily poor design, although these choices predated me at this company.
Speaking as a sole founder with many friends that go their path alone as well, this is not anywhere close to a requirement. There are people for whom this journey is natural and they are more suited, and others for whom they'd prefer or need to be with someone else.
There's no one-size-fits-all solution for founders. Co-founders come with their own set of issues--whether you're on the same page about the company's goals, whether your skill sets are complementary or not, what kind of long term commitment you both have to the problem space, etc.
Been using MemSQL for a enterprise-level financial services client since mid-2017. We have this in production and are running it in a multi-TB cluster. We've not seen ANY of these issues here and are heavy, crazy query users. Their support has been nothing but on-the-spot and very helpful.
Bootstrapped would be any self-funded, usually single-person-founded, company. You might have revenue or not, but the key component is that you are doing this on your own time or money. Not VC-funded.
Don't know what equity take they have, I'm guessing it depends on the size of the investment.
The premise is fine...I have no problem with it. But the default generation of @EqualsAndHashcode literally pulls in the WORLD to generate the output.
The real world scenario we had was this. Lots of POJOs were created, many were simply but a non-trivial number were NOT. Those POJOs could have dozens and dozens of fields. And if you have a key abstraction with say, 86 fields, things get interesting.
Suppose you don't use @EqualsAndHashCode on one of these POJOS with lots of fields, ALL 86 fields are included in the default equals and hashCode methods. They didn't realize this, or didn't care, and as a result, had some serious performance issues because trying to run hashCode on insert to a map when you're hashing 86 fields together might actually take some time inserting 100,000 records... ugh
So in short, it's OK and useful, but you have to understand the side effects of everything to know if it's the right thing for you.
SIDE NOTE: A POJO with 86 fields can be common in financial services when you are representing various kinds of financial trades where gazillions of things are tracked on them...interest rates of note, ratings, security characteristics, etc. That in and of itself isn't necessarily poor design, although these choices predated me at this company.