Apache Cassandra vs Milvus: Choosing the Right Vector Database for Your Needs

Apache Cassandra and Milvus are both vector databases designed to handle high-dimensional vectors, which are numerical representations of unstructured data like text, images, and videos. They differ in their search methodology, data handling capabilities, scalability, flexibility, integration with other tools, ease of use, and cost considerations. Milvus is a specialized vector database designed for high-performance vector search and supports at least 11 indexing methods. It is suitable for AI-centric applications that rely on fast, accurate similarity searches over large volumes of high-dimensional vectors. Milvus offers three deployment options: Milvus Lite, Standalone, and Distributed. On the other hand, Apache Cassandra is a distributed NoSQL database known for its high availability, fault tolerance, and scalability across large clusters. It has added vector search capabilities through DataStax but remains primarily focused on traditional data management. Cassandra's strengths include linear scalability, handling various data types, and integrating with popular big data tools. The choice between Milvus and Apache Cassandra depends on the specific use case and the complexity of the data. Milvus is better suited for AI-heavy applications that require fast vector search capabilities, while Cassandra offers more versatility for environments where vector search is an add-on rather than the core focus.