Hybrid search combines traditional keyword-based search with advanced semantic techniques like natural language processing, machine learning, and word embeddings to provide comprehensive and accurate results. It leverages the strengths of both sparse and dense vectors to handle diverse user queries, from simple exact matches to complex natural language searches. By integrating hybrid search, search engines and databases can deliver enhanced relevance, precision, and adaptability, making it an ideal solution for modern applications such as enterprise environments, e-commerce, digital libraries, and archives.