Engineering challenges of scaling vector search to 500 million data points

A developer outlines the architectural considerations for building a vector search system handling 500 million high-dimensional vectors. The system must support high query traffic, continuous data updates, multi-tenancy, and metadata filtering while maintaining low latency. Key design decisions depend on specific workload requirements like query volume, data freshness, and update frequency. The article argues that choosing an underlying search algorithm is secondary to first defining these measurable performance and operational constraints.