I use it to store a lot of historical time series data that doesn't change once written (at least, not often). I can easily achieve the write performance necess

I use it to store a lot of historical time series data that doesn't change once written (at least, not often). I can easily achieve the write performance necessary to record the data streams live. Since it's all append-only, I don't need to worry about fragmentation. With replication, it's possible to access the data with very high throughput which is useful when the data is being accessed by a cluster, for example. I also use it as a metadata "scratch space" for highly available applications (things where failures are not acceptable and must run for days at a time). Again, with replication and automatic fail overs, I've been able to maintain 100% uptime outside of maintenance windows. Obviously that can't last, but so far it's been >2 years with no major problems. EDIT: I should point out that although the size of the metadata objects can be highly variable, since I usually had a small number of them relative to the time series, fragmentation was still not an issue.