Demystifying the Big Data diaspora
In order to create better storage models for the cloud, more people are using Neo4j to store the wide variety of data
Among the most captivating technology trends of this decade, Big Data clearly stands out. As with any emerging and disruptive technology, there is a lot of hype around it; but unlike others, Big Data is fast maturing and heading towards widespread adoption. It is applicable to a wide gamut of industries like finance, media, technology, retail and healthcare. If anything, it has become even more relevant due to the advent of technology paradigms like cloud, broadband and social media!
Whether you run an e-commerce startup or run products at the scale of Gmail, YouTube or Facebook, you generate gigabytes of data every day, with your storage and compute requirements running into petabytes and hundreds and thousands of CPU cores. The total amount of global digital information created and shared is expected to reach a colossal 4 zettabytes in 2013! And while this deluge of data that we are both floating and sinking in is not really new, what’s new is that this enormous amount of data is now available at our fingertips! It is not stored away and at rest. Cloud-based NoSQL databases have emerged in order to swiftly capture, store, access and retrieve large scale and multi-structured data.
Big Data however is not only characterized by the Volume but also by its Variety (structured, semi-structured and unstructured), Velocity (batch, real time, near real time and streams) and Veracity. It is generated as a result of social media interactions, website clicks, device to device communication – pretty much everything we do, you would say!