Why a Search Platform (Not a Vector Database) is the Smarter Choice for AI Search

As AI search requirements expand, companies must choose between vector databases, search platforms with built-in vector capabilities, and cloud databases with vector add-ons, with each option impacting search accuracy, scalability, and costs differently. While vector databases excel in similarity searches, they often lack comprehensive search features such as ranking and filtering, making traditional search platforms with native vector support a more balanced choice for performance, flexibility, and cost-efficiency. Search platforms like Vespa.ai integrate vector search with advanced ranking, filtering, and scalability, providing a more robust solution for AI-powered search by combining vector similarity with precise search capabilities. Vespa.ai's success is exemplified by Vinted's migration, which improved search performance and reduced costs. Ultimately, while vector databases have their niche uses, a hybrid search platform that incorporates both vector and traditional search elements offers the most effective solution for enterprise AI search needs.