Vector Search as a dedicated service
Blog post from Qdrant
The article explores the debate over the best way to store embeddings for vector search, weighing the benefits of dedicated vector databases against integrating vector capabilities into existing databases. It argues that while integrated solutions may seem appealing due to their convenience, dedicated vector databases offer greater flexibility, scalability, and optimization for vector search tasks, particularly in large-scale systems. The piece also highlights that search engines, often mislabeled as databases, prioritize scalability, speed, and availability differently than traditional databases, which are built on ACID principles. It notes that using a dedicated vector database can avoid performance issues and complex data synchronization problems associated with integrating vector features into a primary database. Ultimately, the article suggests that while simple vector search tasks may not require a specialized database, significant or central vector search functionalities would benefit greatly from a dedicated solution.