Apache Cassandra and Vald are two popular options for handling vector data in AI applications. Cassandra is a traditional NoSQL database that has evolved to include vector search capabilities, while Vald is a purpose-built vector database designed from the ground up for efficient similarity searches. Both systems offer robust scalability but through different mechanisms: Cassandra provides a masterless architecture with tunable consistency, while Vald distributes vector indexes across multiple agents and supports horizontal scaling of memory and CPU resources. The choice between these technologies depends on specific use cases, data types, and performance requirements.