Neo4j wants everything in memory, so the bottlenecks would come after your data-set size outstrips the memory available.

Fast disks are also important for write performance since Neo4j syncs every change - big RAID arrays of SSDs help.

This is one place where Log-Structured-Merge systems can really prove themselves. There is rarely a need to sync on every change as most of them are independent. You can usually gain lots of write-throughput by syncing at the speed the hardware is optimized for and squeezing as many append-only changes in to those logs. At Orly we've spent quite some time looking at ways to deal with these bottle-necks.

if you plan to grow with it, i strongly advise you to battle-test it...