Relational Databases vs Vector Databases

The article discusses the shift from traditional relational databases to specialized databases tailored to specific use cases, such as graph, search, time series, key-value, in-memory, and vector databases. It highlights that while relational databases remain dominant, purpose-built databases are gaining traction due to increasing demands for performance and advanced features. The article also provides an overview of vector databases and compares them with traditional relational databases, emphasizing the importance of selecting the right indexing strategy and benchmarking tools like VectorDBBench to optimize performance. Finally, it outlines various use cases for vector databases, such as Retrieval Augmented Generation (RAG), recommender systems, multimodal similarity search, and molecular similarity search.