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We are not plainly complaining about MongoDB, nor saying it's useless. We are just explaining why it's a poor choice for a specific use case: storing scraped data.

FWIW, we still use Mongo in other internal applications, it's just not the right choice for our crawl data storage backend.

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One issue is that many of these points are design characteristics of MongoDB and should have been known before hand. I am not criticising but it's almost like you did zero research before hand.

Transactions for example have never existed in MongoDB and joins doesn't really make much sense.

Perhaps they did their research on MongoDB and knew all the limitations, but thought to themselves "meh, I can solve all that in the application code", and eventually found out it wasn't so easy to handle transactions and joins in the code?

After all, developers are rather susceptible to the "don't tell me I can't do that" behavior.

How was the evaluation process that led to using MongoDB in the first place?

At some point you must have compared it to, say, Postgres – which is what the section before the summary hints to.

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