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by Goldcap 5334 days ago
Just reading about your transactional volume, it seems like at it's face MongoDB wouldn't be a good fit for this project. 30k per second is not anywhere MongoDB pretends to live, I think by their own admission. And Sharding in MongoDB, while being called a core feature, was bolted on after core development, probably intended to give Mongo some credibility with those who want it to be more scalable. IMHO if you need that kind of scalability, you're already straying from the Mongo Niche, 2.0.0 notwithstanding.

So agreeing with a point earlier, if you don't like a write lock implementation, and have concerns about scaling, and have a huge transactional volume, just really not something that fits well with MongoDB.

I've been using Mongo now (currently using 1.8) for three (is it almost three now?) years, 2 million hits/day, with a replicated set, and while I've needed maintenance, reindexing, and (gasp) restarts on occasion, never had any of the problems identified by the author of this post.

Bottom line, sounds to me like someone was in over someone's head from an architectural standpoint, made a bad choice of MongoDB, and then blamed 10gen for his own lack of foresight. So while I empathize with the struggle, I fault him for not knowing his options in advance, TESTING first, then betting the farm on a fairly new opensource codebase.

LOTS of other database solutions that would scale better. Analyzing lots and lots of transactional stateless data with MongoDB map-reduce? Well, just kinda like killing yourself by trying to sprint up from the bottom of the Grand Canyon. "You really tried to do that?"

1 comments

there's an initial hadoop plugin for mongo that might be a better fit for doing map-reduce over large datasets https://github.com/mongodb/mongo-hadoop