The main difference between these noations is the part of code execution they describe like upper bound, lower bound or tight bound.

Big O gives an upper limit on how fast the time can grow or we can simply say that it gives the highest limit that the execution of this code can never take more time than this in any of the case or with any input size.

Big-Ω gives the lower bound or it describes the best possible growth rate or we can say that it tells us that the algorithm will take atleast this much time in all the cases now matter how big or how small the size of input is. it is the best case because when on a given input the algorithm takes minimum time the execution is faster.

Big-Θ is used when both upper and lower bounds are the same. it means that the algorithms growth rate is tightly bound on both the sides.