Big Data possibly now has become the most used term in the tech world for this decade. Everybody is talking about it and everybody have their own understanding towards it which has made its definition quite ambiguous. Let us deconstruct this term with a situation. Suppose you are creating a database for movie ratings where rows indicate user IDs, columns indicate movies and the values of the cells indicates rating(0-5) given by user to the corresponding movie. Now this data is likely to be sparse as you can’t have a situation where all users have rated all movies. In real world situation you can conceive the sparsity of this database and the cost it takes to store this huge database/matrix.
DynamoDB offered by Amazon pioneered the idea of Eventual Consistency as a way to achieve higher availability and scalability.
Big dataset is broken in chunks and these chunks are then sent to different machines. Some replicas of these chunks also sent to these machines to address fault-tolerance. So the two requirements which we need to deal with here are:-