Our picks for the best of the best.
As we close the book on 2016 and start writing a new one for 2017, it’s a good time to reflect on the products we’ve liked best over the past year. In these pages, you’ll find old friends, stalwart standbys and newcomers you may not have even thought about.
Our contributors are experts in the fields of virtualization and cloud computing. They work with and study this stuff on a daily basis, so a product has to be top-notch to make their lists. But note that this isn’t a “best of” type of list; it’s merely an account of the technologies they rely on to get their jobs done, or maybe products they think are especially cool or noteworthy.
Jon Toigo on Adaptive Parallel I/O Technology
In January, DataCore Software provided proof that the central marketing rationale for transitioning shared storage (SAN, NAS and so on) to direct-attached/software-defined kits was inherently bogus. DataCore Adaptive Parallel I/O technology was put to the test on multiple occasions in 2016 by the Storage Performance Council, always with the same result: parallelization of RAW I/O significantly improved the performance of VMs and databases without changing storage topology or storage interconnects. This flew in the face of much of the woo around converged and hyper-converged storage, whose pitchmen attributed slow VM performance to storage I/O latency — especially in shared platforms connected to servers via Fibre Channel links.
While it is true that I like DataCore simply for being an upstart that proved all of the big players in the storage and the virtualization industries to be wrong about slow VM performance being the fault of storage I/O latency, the company has done something even more important. Its work has opened the door to a broader consideration of what functionality should be included in a properly defined SDS stack.
In DataCore’s view, SDS should be more than an instantiation on a server of a stack of software services that used to be hosted on an array controller. The SDS stack should also include the virtualization of all storage infrastructure, so that capacity can be allocated independently of hypervisor silos to any workload in the form of logical volumes. And, of course, any decent stack should include RAW I/O acceleration at the north end of the storage I/O bus to support system-wide performance.
DataCore hasn’t engendered a lot of love, however, from the storage or hypervisor vendor communities with its demonstration of 5 million IOPS from a commodity Intel server using SAS/SATA and non-NVMe FLASH devices, all connected via Fibre Channel link. But it is well ahead of anyone in this space. IBM may have the capabilities in its SPECTRUM portfolio to catch up, but the company would first need to get a number of product managers of different component technologies to work and play well together.
Dan Kusnetzky on SANsymphony and Hyper-converged Virtual SAN
Why I love it: DataCore is a company I’ve tracked for a very long time. The company’s products include ways to enhance storage optimization, storage efficiency and to make the most flexible use of today’s hyper-converged systems.
The technology supports physical storage, virtual storage or cloud storage in whatever combination fits the customer’s business requirements. The technology supports workloads running directly on physical systems, in VMs or in containers.
The company’s Parallel I/O technology, by breaking down OS-based storage silos, makes it possible for customers to get higher levels of performance from a server than many would believe possible (just look at the benchmark data if you don’t believe me). This, by the way, also means that smaller, less-costly server configurations can support large workloads.
What would make it even better: I can’t think of anything.
Next best product in this category: VMware vSAN