Vector databases (Vector DBs) are a foundational and critical application layer for injecting information into large language models (LLMs). Although different companies have proposed various vector databases, no academic workshop has previously existed to discuss these systems comprehensively. This workshop aims to foster discussions on vector databases from various perspectives, ranging from mathematical theories to implementation-level optimizations. Topics covered in the workshop include retrieval-augmented generation (RAG), algorithms and data structures for approximate nearest neighbor search (ANN), data management systems for handling vector data, query languages, and embedding models. Furthermore, the workshop will also function as a platform for companies and researchers working on vector databases to present technical details (white papers) and exchange ideas.