When you say that, this is what I hear:
> MongoDB is the quickest way to accrue large quantities of technical debt.
In this analogy, fast accrual of debt leads to one place: bankruptcy. Which, in software engineering, is the ground-up rewrite.
When you say that, this is what I hear:
> MongoDB is the quickest way to accrue large quantities of technical debt.
In this analogy, fast accrual of debt leads to one place: bankruptcy. Which, in software engineering, is the ground-up rewrite.
Some projects with this kind of popularity (n.b.: not the ones I mentioned by name) are designed like shit, do irrational things, have performance problems, have security problems, whatever. But they have been used and they are usable and you can find documentation and experts to deal with them.
Bankruptcy can be just that -- bankruptcy and loss of job, liquidation of a company.
It can go either way. Spending years perfecting a product and polishing it to 100% only wake up and find out that someone else used something crappy fast and easy to setup thing, got the product out, and started getting real customers. Now they have enough to go double their team and start rewriting if they want.
Or picking something fast and easy to setup and after getting a few initial customers finding that scaling out doesn't work. The site crashes and everything is going to shit, data is silently corrupted, it has already been backed up and overwrote older backups and customers are leaving for something else, maybe not as flashy and cool, but something that works.
What's wrong with using MongoDB to screw around while you are developing it? It's not like you have to marry it. Figure out what schema you are going to be using, and then write your table layouts for Postgres.
MongoDB has a completely different data model to PostgreSQL. You can't just build your app around one approach and then trivially move to another.
Pick the database for the data model not the other way around.
(^ that means I agree).
This idea that you can arbitrarily switch between database X and database Y with radically different models is a really harmful fallacy. Code which attempts to ‘abstract away the details’ is often leaky, buggy, complex, and just as prone to tight coupling as any other solution.
At the very least, such has been my experience. And I think certain individuals have a policy of downvoting those comments they disagree with rather than explaining their counterpoints in a comment.
public interface IAnalysisService
{
Guid CreateAnalysis(Guid ownerId, string name);
void LoadingAnalysisInputs(Guid analysisId);
void RequestAnalysis(Guid analysisId, string number, IEnumerable<Records> inputs);
Guid CreateAndRequestAnalysis(Guid ownerId, string name, string number, params Records[] inputs);
Guid CreateAndRequestAnalysis(Guid ownerId, string name, string number, IEnumerable<Records> inputs);
Analysis FindAnalysis(Guid analysisId);
Analysis FindAnalysisForProcessing(Guid analysisId);
void CompletedAnalysis(Guid analysisId, AnalysisResults results);
void FailedAnalysis(Guid analysisId, string reason, params object[] args);
}
These methods implement some business rules, do some database work and throw a few messages onto a service bus. Why is it so hard to believe that the database implementation for any of these methods affects the consumers? Here's a sample implementation: public void FailedAnalysis(Guid analysisId, string reason, params object[] args)
{
AnalysisRepository.Failed(analysisId, string.Format(reason, args));
Bus.Send(new AnalysisCompleted {AnalysisId = analysisId});
}
I don't see any obvious bugs, complexity or leaky abstractions.