Alright, you caught me! I never actually mistook Big Data for Big Daddy, but I needed to somehow preface how hopelessly unqualified I am to be anyone’s Big Data tour guide. My insecurity is further entrenched by prophecies that Big Data is the next chapter in tech, or claims that big data will “replace ideas, paradigms, organizations, and ways of thinking about the world.” As if the technical jargon wasn’t enough to have me running for the hills there are now global philosophical implications. So where does one begin when looking to understand Big Data? Well of course, start with its intimidating-sounding primary feature!
“Not only Structured Query Language” (NoSQL) is database management system (DBMS) that is integral to Big Data. This veritable “Sid Vicious” of DBMSs is identified by its very lack of adherence to the widely used relational database system. By refusing to conform to the relational databases of yore NoSQL stands alone in its ability to store many different types of information--and lots of it.
NoSQL finds much of its strength in its distributed architecture, a characteristic that allows NoSQL to be everywhere and nowhere at the same time. Distributed architecture means that instead of data being stored on singular, massive, expensive servers, the data is spread out amongst many different commodity servers. By "distributing" the data you reduce the risk of failure and increase efficiency. Given that NoSQL is concerned with the storage of ever-growing amounts of data, scalability is paramount. Thankfully, a distributed architecture can be expanded to any capacity.
From the looks of it, it appears there would be no Big Data if it weren’t for the development of NoSQL. Or perhaps there would still be Big Data but it wouldn’t be the paradigm shifting, global perspective changing technology we’ve been promised. Which begs the question, if NoSQL didn’t break out of the relational database “box,” would big data be concerned with anything of importance?