I'm using it for the analytics suite at my company (large ecommerce multinational).
Its weird at first, coming from a background of Access then SQLite then MySQL/PHPMyAdmin but you get used to it. I essentially treat it like a gigantic python dictionary object.
The sharding is too much of a ball-ache to set up so I've created an optimal way of distributing/mapping files across our cluster to make use of all machines.
Data integration is nice. Making sure there's no temptation to output each integrated line to the terminal, pymongo and its C extensions can integrate a ~500 byte record in ~0.0001 seconds.
Basically the main advantage is not having a schema whatsoever - you can just add random attributes to documents whenever the hell you want. But later you have to be careful with exception handling since documents might not have the attributes you expect.
Its weird at first, coming from a background of Access then SQLite then MySQL/PHPMyAdmin but you get used to it. I essentially treat it like a gigantic python dictionary object.
The sharding is too much of a ball-ache to set up so I've created an optimal way of distributing/mapping files across our cluster to make use of all machines.
Data integration is nice. Making sure there's no temptation to output each integrated line to the terminal, pymongo and its C extensions can integrate a ~500 byte record in ~0.0001 seconds.
Basically the main advantage is not having a schema whatsoever - you can just add random attributes to documents whenever the hell you want. But later you have to be careful with exception handling since documents might not have the attributes you expect.