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There's always a trade-off somewhere. Does it take 3x more RAM/storage? Does it make record insertion extremely slow?

To tolerate f failures, we need to have f+1 replicas of the data. This implies increased storage, but the f parameter is entirely up to the application.

Record insertion affects all replicas of the data, so latency increases with replication.

The first graph on the performance page (http://hyperdex.org/performance/) shows that a 100% insertion workload will exhibit higher latency (and thus lower throughput for a fixed number of synchronous clients). Write-mostly workloads are slower, but I wouldn't say "extremely slow."

From what I gather skimming through the paper, you should be more concerned comparing HyperDex to Riak, than to Cassandra or MongoDb. The potential use cases seem to be quite different for the last mentioned.

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