When it comes to topic modeling, named entity recognition, and entity extraction. Is Spacy the go to library or is Bert used or both?

I will be working on a project in which we will be given many documents. And we want to eventually build a semantic search. I am new to NLP. I have been reading up on it for the past several days and watching tutorials. Spacy seems to do score similarity between documents and what not so I figured I will use that, but read that google and many people use BERT for topic modeling, so I am not sure which to use or if I use them in tandum with each other.