We're (Inkling) successfully using Cassandra in production to store most of our data. I wrote the first version of our data store modeled off of FriendFeed's a

We're (Inkling) successfully using Cassandra in production to store most of our data. I wrote the first version of our data store modeled off of FriendFeed's architecture (back when we were five people). There is an excellent blog post about it here: http://bret.appspot.com/entry/how-friendfeed-uses-mysql http://bret.appspot.com/entry/how-friendfeed-uses-mysql When Cassandra came along, we had long debates internally about the risk of hitching ourselves to their wagon. Eventually we decided that an open source project with a similar (enough) architecture to what we'd been building ourselves was preferable to maintaining a python library in-house. So far we have no regrets. We have had no production issues and we have an architecture that is built to handle a large amount of incoming data (every note and highlight you take in an Inkling book is synched to our servers). We had already stripped away most SQL functionality by using FF's architecture, so we didn't lose much. And we gained a lot - the ability to tune the durability of different writes depending on the use case, far better fault tolerance, a conceptually simpler indexing strategy, etc. It definitely has a learning curve - error and status reporting is not wonderful, you generally need to be over-provisioned as a strategy, etc. But I'm happy we learned those lessons sooner rather than later - I'd hate to scramble to implement Cassandra in a strained production environment (my sympathies to a certain website who suffered through this).