SingleStore vs Apache Cassandra Choosing the Right Vector Database for Your AI Apps

A vector database is a specific type of database designed to store and query high-dimensional vectors, which encode complex information such as the semantic meaning of text or visual features of images. Vector databases play a pivotal role in AI applications by enabling efficient similarity searches, allowing for more advanced data analysis and retrieval. SingleStore and Apache Cassandra are two popular vector databases that offer different approaches to vector search, with SingleStore having native vector search capabilities and Cassandra offering vector search through its Storage-Attached Indexes (SAI) feature. Both databases have strong scalability features but differ in their design approach, with SingleStore distributing data across nodes for horizontal scaling and Cassandra's masterless architecture providing high availability. SingleStore integrates vector search with standard SQL syntax, making it more familiar to teams with SQL backgrounds, while Cassandra requires learning its own query language and data modeling concepts. The choice between SingleStore and Apache Cassandra depends on technical requirements and constraints, with SingleStore suitable for companies needing ACID compliance and Cassandra ideal for use cases requiring horizontal scalability and high availability. Thorough benchmarking with VectorDBBench or other tools will be key to making an informed decision between these two powerful approaches to vector search in distributed database systems.