Data deduplication has been around for a while now with both companies and individuals looking for ways to save storage (on local machines/clouding computing sites) or bandwidth when required to transfer data over network. In modern day most of the advances have been done in variable-size content-based chunking, which is more effective on identifying duplicate records than fixed-size chunking agreeing to later ponders, and bargains with the issue of boundary-shift during the upload or deletion of files. Since the chunking stage has a direct impact on finding redundancy, Content-Defined Chunking (CDC) algorithm has proved to be more effective on performance and deduplication ratio. Many researchers have and continue to work on ways on how to fully utilize the CDC algorithm. This review will discuss on how various researchers developed their own unique algorithms based on variable-size content-based chunking.