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How we use Redis at Bump (bu.mp)
59 points by rs on July 16, 2011 | hide | past | favorite | 10 comments



I'm curious as to what hardware specs are used for these various cases.

How much RAM? How many instances per server? How many servers?


We also find Redis perfect in a whole range of scenarios.

I like Redis because it's simple enough that I feel I easily understand what's going on (i.e. performance is predictable), yet powerful enough to do pretty much everything I want.

From a productivity point of view, the only scenarios that come to mind in which I've found myself thinking a relation database would be better are:

1. Indices: In scenarios where you could use an index with a relational database you need to create and manage this by hand in Redis. This takes time, and increases application complexity.

2. Transactions: They are far less flexible in Redis. Effectively you must get/WATCH all your data before entering a MULTI/EXEC block for setting. I've found organizing code for this can sometimes be very constraining. Of course on the upside, Redis is forcing you to be efficient.


Half the time, simply having transactional behavior on the application side is "enough" reliability for most.

App node goes down? Meh. If it's important, it'll get submitted again.


I know redis is great, but I wondering what this

""" [persistence] This is something that every database has trouble with and Redis is no exception. """

is supposed to mean. To me it seems that most databases deal with persistence just fine.


To read some previous discussion of this article, check here: http://news.ycombinator.com/item?id=2222431

(We're still using Redis :-)


The author mentions always giving MongoDB its own server. Can anyone shed some light on that?


For production apps, afaik that's always been a rule of thumb for any kind of db, be it rdbms, nosql, etc.


Cool use with BSON as mentioned in the article:

http://bsonspec.org/


The problem with BSON is that the Python modules that implement it are incredibly slow when it comes to nested dicts. In fact, if you nest too deeply the BSON encoder will just seg fault.


Thanks for the warning.




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