Hitachi’s VSP vs. VMAX

Today’s announcement of Hitachi’s VSP brings another round to the competition between EMC and Hitachi/HDS in the enterprise. VSP’s recent introduction which is GA and orderable today, takes the rivalry to a whole new level.

I was on SiliconANGLEs live TV feed earlier today discussing the merits of the two architectures with David Floyer and Dave Vellante from Wikibon. In essence, there seems to be a religious war going on between the two.

Examining VMAX, it’s obviously built around a concept of standalone nodes which all have cache, frontend, backend and processing components built in. Scaling the VMAX, aside from storage and perhaps cache, involves adding more VMAX nodes to the system. VMAX nodes talk to one another via an external switching fabric (RapidIO currently). The hardware although sophisticated packaging, IO connection technology and other internal stuff looks very much like a 2U server one could purchase from any number of vendors.

On the other hand, Hitachi’s VSP is a special built storage engine (or storage computer as Hu Yoshida says). While the architecture is not a radical revision of USP-V, it’s a major upleveling of all component technology from the 5th generation cross bar switch, the new ASIC driven Front-end and Back-end directors, the shared control L2 cache memory and the use of quad core Xenon Intel processors. Much of this hardware is unique, sophistication abounds and looks very much like a blade system for the storage controller community.

The VSP and VMAX comparison is sort of like a open source vs. closed source discussion. VMAX plays the role of open source champion that largely depends on commodity hardware, sophisticated packaging but with minimal ASICs technology. As evidence of the commodity hardware VPLEX EMC’s storage virtualization engine reportedly runs on VMAX hardware. Commodity hardware lets EMC ride the technology curve as it advances for other applications.

Hitachi VSP plays the role of closed source champion. Its functionality is locked inside proprietary hardware architecture, ASICS and interfaces. The functionality it provides is tightly coupled with their internal architecture and Hitachi probably believes that by doing so they can provide better performance and more tightly integrated functionality to the enterprise.

Perhaps this doesn’t do justice to either development team. There is plenty of unique proprietary hardware and sophisticated packaging in VMAX but they have taken the approach of separate but equal nodes. Whereas Hitachi has distributed this functionality out to various components like Front-end directors (FEDs), backend directors (BEDs), cache adaptors (CAs) and virtual storage directors (VSDs), each of which can scale independently, i.e., doesn’t require more BEDs to add FEDs or CAs. Ditto for VSDs. Each can be scaled separately up to the maximum that can fit inside a controller chasis and then if needed, you can add a whole another controller chasis.

One has an internal switching infrastructure (the VSP cross bar switch) and the other uses external switching infrastructure (the VMAX RapidIO). The promise of external switching like commodity hardware, is that you can share the R&D funding to enhance this technology with other users. But the disadvantage is that architecturally you may have more latency to propagate an IO to other nodes for handling.

With VSP’s cross bar switch, you may still need to move IO activity between VSDs but this can be done much faster and any VSD can access any CA, BED, FED resource required to perform the IO so the need to move IO is reduced considerably. Thus, providing a global pool of resources that any IO can take advantage of.

In the end, blade systems like VSP or separate server systems like VMAX, can all work their magic. Both systems have their place today and in the foreseeable future. Where blades servers shine is in dense packaging, high power cooling efficiency and bringing a lot of horse power to a small package. On the other hand, server systems are simple to deploy and connect together with minimal limitations on the number of servers that can be brought together.

In a small space blade systems probably can bring more compute (storage IO) power to bear within the same volume than multiple server systems but the hardware is much more proprietary and costs lots of R&D $s to maintain leading edge capabilities.

Typed this out after the show, hopefully I characterized the two products properly. If I am missing anything please let me know.

[Edited for readability, grammar and numerous misspellings – last time I do this on an iPhone. Thanks to Jay Livens (@SEPATONJay) and others for catching my errors.]