7 Storage Vendors Keeping Up With Big Data

One of the more confusing aspects of a big-data project is figuring out what type of storage to use. Wading through all the technical terms and marketing-speak is time consuming and you often end up confused and frustrated as opposed to enlightened. In this slideshow, we provide some shopping guidance for big-data storage. There are many storage vendors pushing their particular products and architectures. We list seven that are adept at supporting big data and explain how they can be good options in certain scenarios.

Your choice in a storage platform will mostly revolve around the type of data being stored, how it is collected, and what type of analytics framework is used to collect and perform data mining. Some popular analytics frameworks include Spark, Hadoop, Flink, and NoSQL.

There are several different types of storage solutions for big data, depending on your environment. From a network-attached storage perspective, clustered/scale-out NAS remains a popular choice. Object-storage systems also are gaining traction as storage optimized for hyperscale computing environments. Last, there's a niche market in big-data analytics that can take advantage of pre-configured and easy to deploy hyperconverged platforms, which include compute, network and storage in one neat little single-vendor bundle.

That said, let's take a look at which storage vendors and products we're excited about when it comes to supporting big-data initiatives. Our section includes the typical players that have been in the storage space for years. But we also include some up-and-coming vendors and technologies that are making an impact on the rapidly growing and changing world of big data.

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