As data rapidly increases in today’s information-based economy, storage demands are increasing right along with them. The cost of hardware alone makes it too expensive to build out traditional storage infrastructure, making its rate of scale too slow to be an effective option. Being able to expand rapidly is a key element of any organization’s growth strategy. Enterprises today need flexible, scalable storage approaches if they hope to keep up with rising data demands.
Software-defined storage (SDS) offers the needed flexibility. In light of the varied storage and compute needs of organizations, two SDS options have arisen: hyperconverged and hyperscale. Each approach has its distinctive features and benefits, which are discussed below.
Hyperwhat? Defining Our Terms
First, it’s important to understand what came before hyperconverged and hyperscale approaches. Converged storage combines storage and computing hardware to increase delivery time and minimal the physical space required in virtualized and cloud-based environments. This was an improvement over the traditional storage approach, where storage and compute functions were housed in separate hardware. The goal was to improve data storage and retrieval and to speed the delivery of applications to and from clients.
Converged storage infrastructure uses a hardware-based approach comprised of discrete components, each of which can be used on its own for its original purpose in a “building block” model. Converged storage is not centrally managed and does not run on hypervisors; the storage is attached directly to the physical servers.
Hyperconverged storage infrastructure, on the other hand, is software-defined. All components are converged at the software level and cannot be separated out. This model is centrally managed and virtual machine-based. The storage controller and array are deployed on the same server, and compute and storage are scaled together. Each node has compute and storage capabilities. Data can be stored locally or on another server, depending on how often that data is needed.
In these ways, hyperconverged storage increases flexibility and agility – precisely what is needed in order to effectively and efficiently manage today’s data demands. It also promotes cost savings. Organizations are able to use commodity servers, since software-defined storage works by taking features typically found in hardware and moving them to the software layer. Organizations that need more 1:1 scaling would use the hyperconverged approach, and those that deploy VDI environments. The hyperconverged model is storage’s version of a Swiss Army knife; it is useful in many business scenarios. It is one building block that works exactly the same; it’s just a question of how many building blocks a data center needs.
So why, then, is there a need for hyperscale storage? It’s a new storage approach created to address differing storage needs. Hyperscale computing is a distributed computing environment in which the storage controller and array are separated. As its name implies, hyperscale is the ability of an architecture to scale quickly as greater demands are made on the system. This kind of scalability is required in order to build big data or cloud systems; it’s what Internet giants like Amazon and Google (News - Alert) use to meet their vast storage demands. However, software-defined storage now enables many enterprises to enjoy the benefits of hyperscale.
One of these benefits is reduced total cost of ownership, since commodity servers are typically used and a data center can have millions of virtual servers without the added expense that this number of physical servers would require. Data center managers want to get rid of refrigerator-sized disk shelves that use NAS and SAN solutions, which are difficult to scale and very expensive. With hyper solutions, it is easy to start small and scale up as needed. Using standard servers in a hyper setup creates a flattened architecture. Less hardware needs to be bought, and it is less expensive. Hyperscale enables organizations to buy commodity hardware. Hyperconverged goes one step further by running both elements—compute and storage—in the same commodity hardware. It becomes a question of how many servers are necessary.
Hyperconverged or Hyperscale? Your Choice
Running a hyperconverged storage model is essentially having one box with everything in it; hyperscale has two sets of boxes, one set of storage boxes and one set of compute boxes. It just depends what the architect wants to do, according to the needs of the business. A software-defined storage solution would take over all the hardware and turn it into a type of appliance, or it could be run as a VM – which would make it a hyperconverged configuration.
Fortunately, this is not an either-or proposition. Data center architects can employ a combination of hyperconverged and hyperscale infrastructures to meet their needs. Because those needs will change, and the flexibility that software-defines storage enables will continue to help organizations effectively manage whatever lies on the horizon in terms of data requirements. And these hyper solutions will do so in a cost-effective way as well – icing on the storage cake.