Apache Cassandra and Vespa are two popular options for handling vector data in AI applications. While both databases offer scalability, performance, and flexibility, they differ in their approach to search methodology, data handling, and ecosystem integration. Cassandra is best suited for large-scale distributed data applications with basic vector search functionality, while Vespa excels in search-heavy applications requiring advanced multi-modal search capabilities. Choosing between the two depends on whether your focus is distributed data management or powerful, real-time search capabilities.