Both vector search and semantic search are used to improve the relevance of your search results. However, they're orthogonal features, meaning you can use them independently or together. They both use deep neural networks (DNNs) to improve relevance, but the models and infrastructure are different for each feature.
You can use vector search and semantic search together if the search request contains a text query - hybrid search. The search engine uses Reciprocal Rank Fusion to merge results from both vector and term queries before semantic search reranking is applied.