Greedy algorithms are a fundamental category of algorithms in mathematics and computer science, characterized by their iterative, locally optimal decision-making approach, which aims to find global optima. In this review, we will discuss two greedy algorithms. First, we will talk about the so-called Relaxed Greedy Algorithm in the context of dictionaries in Hilbert spaces analyzing the optimality of definition of this algorithm and, next, we give a general overview of the Thresholding Greedy Algorithm and the Chebyshev Thresholding Greedy Algorithm with regard to bases in p-Banach spaces with $0 < p \leq 1$. In both cases, we pose some questions for future research.