{"id":601,"date":"2017-10-13T08:09:41","date_gmt":"2017-10-13T15:09:41","guid":{"rendered":"https:\/\/www.kenwalger.com\/blog\/?p=601"},"modified":"2017-10-13T08:09:41","modified_gmt":"2017-10-13T15:09:41","slug":"big-data-nosql-great-coupling","status":"publish","type":"post","link":"https:\/\/www.kenwalger.com\/blog\/nosql\/big-data-nosql-great-coupling\/","title":{"rendered":"Big Data and NoSQL: A Great Coupling"},"content":{"rendered":"

Big data has been a buzzword and topic of conversation for many years. Similarly, the idea of NoSQL as a data store versus “traditional” relational databases is a frequently debated topic. With all of the conversation about these topics, it is important to ask a few questions. What is this thing called big data? Are NoSQL databases like OrientDB<\/a> a good fit for big data? Let’s explore these questions and learn why NoSQL can indeed be a\u00a0great<\/strong> fit for big data.<\/p>\n

Big Data Defined<\/h3>\n

A popular definition of big data states:<\/p>\n

Any quantity of data which is too large or complex that traditional computing power is inadequate to deal with.<\/p><\/blockquote>\n

While this makes sense, it is important to note that the concept of big data is\u00a0somewhat<\/em> relative. It likely has a much different meaning and concept for Farmer Bob, the local apple farmer than it does for Tree Top<\/a> juice company. In the technology realm, we often think of companies like Facebook or Netflix in relationship to big data processing. But every industry is capturing more and more data.<\/p>\n

Think about our apple farmers. Some of the data they might want to be collecting would be soil moisture levels, air & soil temperatures, rainfall, the type of apple being grown, the geo-location of the trees, soil pH, fertilizer applications, pollination\u00a0events, just to name a few.<\/p>\n

In the data industry, there are four common dimensions of big data. The so-called\u00a04 V’s<\/a>, volume, variety, velocity, and veracity.<\/p>\n

4 Dimensions of Big Data<\/h5>\n