Choosing between vector search and traditional search depends on the specific needs of your application. Vector search is advantageous when dealing with unstructured data, such as text, images, or audio, where the semantic meaning is more critical than exact word matches. It is particularly useful in applications requiring natural language understanding, like chatbots, recommendation systems, and semantic search engines.
If your use case involves finding similar items or understanding the context of a query, vector search is the better choice. It is also ideal for scenarios where approximate nearest neighbors search is needed, as it efficiently narrows down potential matches in a vast search space.
However, if your application involves structured data with well-defined fields or requires exact matches, traditional keyword search might be more suitable due to its lower computational cost and simplicity. Ultimately, the choice between vector and traditional search should be guided by the nature of the data and the desired search experience.