Russ Miller runs a monster of a server cluster that eats storage at an incredible rate. The bandwidth requirements alone on his 22TFLOPS system force Miller to look outside the storage box, so to ...

As file sizes and data sets grow into the terabyte and petabyte range, users are looking for a method for storing, accessing and sharing the files among different hosts. That’s where clustered and ...

Nebulon’s “cloud-defined storage” – which can build a cloud-defined storage cluster with local I/O using commodity hardware – is now a purchase option using servers from Dell, HPE, Lenovo or ...

Big Data analytics requirements have forced a huge shift in data storage paradigms, from traditional block- and file-based storage networks to more scalable models like object storage, scale-out NAS ...

The rationale for deploying a clustered storage system is in many ways similar to that of deploying clustered servers: You get better scalability, both for capacity and performance, and more ...

The storage industry is continually changing. In fact, that change is so fast that new SSDs or all-flash storage arrays no longer turn heads like they did even a year ago, and bringing storage to the ...

It's a while off yet but I'm already thinking about what we do when our current SAN (P4000) is due to be replaced. What I'd like is something node, not frame based, that can be installed onto ...

It may not seem like it, but Oracle is still in the high-end server business, at least when it comes to big machines running its eponymous relational database. In fact, the company has launched a new ...

An already-working open source database project could let other web companies join Google for bragging rights as the owners of a thousand-node database cluster. Moving the project from in-house to ...

IDC estimates that upwards of 80% of business information is likely to be formed of unstructured data by 2025. And while “unstructured” can be something of a misnomer, because all files have some sort ...

K-means is comparatively simple and works well with large datasets, but it assumes clusters are circular/spherical in shape, so it can only find simple cluster geometries. Data clustering is the ...