QNAP Enterprise NAS

Both are excellent. Synology is prized for ease of operation and its software suite; QNAP often leads on raw performance and flash options. We recommend based on your priorities. A useful way to decide: if the storage is mainly a dependable home for files and backups that a lean team has to run, weight ease of operation; if it sits in the path of a workflow where people wait on it, weight performance and network options. We will quote both against the same requirement so the comparison is real.

Yes, QNAP provides iSCSI block storage suitable for VMware and Hyper-V datastores, with snapshot protection. Two things to settle in the design: the number and speed of the links carrying that traffic, since a datastore shares its network with everything else unless you separate it; and how the array's snapshots relate to the hypervisor's, because a storage snapshot taken mid-write captures a crash-consistent image rather than a clean one unless the two are coordinated.

For latency-sensitive or high-throughput workflows, yes. For general file storage, hybrid may be more economical. We help you decide. The clearest indicator is concurrency: if many clients or many processes read at once (a shuffled data loader, an edit suite, a virtualization host), flash is answering a problem that adding disks cannot. If one user streams one large file at a time, a well-populated hybrid array will keep up for far less money.

Usually because the benchmark was sequential and the workload is not. A single large sequential read is the easiest thing you can ask storage to do; real workloads issue many small requests at once, from several clients, mixed with writes. The other common cause is the network: a synthetic test run on the array itself never touches the wire, so it will not show you a link that is already saturated.

For a single GPU server or a small team it can be a reasonable dataset store, particularly all-flash and on a fast link. For multi-node training it is the wrong tool, and we will say so: aggregate read demand scales with the number of nodes pulling data at once, and checkpoint writes arrive as a burst from every rank simultaneously, which is a parallel storage problem rather than a NAS one. That storage is specified with the cluster, alongside the systems at /products/gpu-servers.

They consume space in proportion to how much data changes, not to how much data you have. A quiet file share can retain snapshots for a long time cheaply; a busy virtualization datastore or an active dataset directory can consume a surprising amount, because every changed block is retained for as long as a snapshot references it. We size headroom for the retention you actually want rather than leaving it to be discovered when the volume fills.