A Comparative Analysis of Streaming Algorithms: Memory Efficiency and Accuracy Under Fixed Budgets

Streaming algorithms go through a massive data set to point out specific data entries under a specific protocol or find out their probabilistic cardinalities through sub-linear means. This research paper aims to go through six specific streaming algorithms, their efficiency, and accuracy under a fixed budget of 64kb, as well as the amount of memory required to reach a targeted error percentage. The code to test this was written in Python, and the formulas are from sources mentioned in the paper.