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Understanding Big Data Storage

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The term big data has emerged and has been a major talking point in the business IT realm. However, in the mainstream business environment, very little is known about big data and more so about big data storage. In the interest of understanding what the fuss is all about, we will take an in-depth review if big data with a specific interest being its storage.

Big Data: What Is It?

Big data describe data that is enormous volumes of data that is gathered. It comprises of the traditional structured data, such as sales report and unstructured data, for instance, data gathered from social media. Additionally, the big data also entails an element of analysis of the large data volume collected with an aim of extracting information that is termed as actionable.

Elements Indicative Of A High-Quality Big Data Storage Systems

In essence, a big data storage system like this one must feature capabilities such as:

#1. Handling large amounts of data in an efficient manner

#2. Scaling to meet growth demands

#3. High-Performance Computing (appropriate input/output operations per second), and

#4. Highly secure data storage.

One of the most basic functions of the system is to handle a large amount of data that is generated and used by organizations. The second bit is also of utmost importance since the volume of both structured and unstructured data are increasing at exponential rates of up to 50% annually. Thus, big data storage systems must be able to scale up with increased data accumulation, lest storage inefficiencies crop up.

Since computation and analysis of the data are required within a short time span, the storage system should be capable of providing real-time analysis and therefore real-time responses to queries. It is not only a matter of storing the structured data (such as sale reports) and the unstructured data (prevailing weather during the sales), it is also about using these data sets to provide what is referred to as actionable information – information that can be used to make decisions by business managers.

Finally, the storage and handling of the big data should be done in secure environments and secure means. Big data usually contain sensitive information regarding organization operations. It, therefore, goes without saying that the storage should always be secure.

Variety Of Big Data Compute/Storage

The verity of storage architecture that can be deployed to store big data include:

Hyperscale Compute/Storage architecture – this is an architecture that is widely used by big organization dealing big data, including Google and Facebook. The system is composed of many simple storage nodes, often time commodity servers that have direct-attached storage (DAS). This type of architecture has been a preserve of large companies. However, storage suppliers have recognized the opportunity in Hyperscale architecture and are looking to get in the market.

Scale-Out Nas – in this architecture, storage nodes are usually daisy-chained together thus allowing the system to scale-up its processing power or storage power.

Object storage – this architecture features systems whereby data is stored in a flat data structure with every file being given a unique ID. Replacing the traditional hierarchical data structure allows the system to store and process a large volume of data.

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