PostgreSQL Functions Enable Image Similarity Search via Euclidean Distance

A technical walkthrough published on DEV Community by developer @rpi1337 explains how two custom PostgreSQL functions can power image similarity comparisons inside a database. The first function, get_vector_values, converts a JSONB array of CIELAB color space values into a flat real-number array, creating a vector signature for a window of image data. The second function, distance, applies the standard Euclidean distance formula to two such arrays, returning a score where zero indicates identical images. Together, the functions support a sliding window comparison technique useful for detecting duplicate or visually similar images. The article notes that while functional, this PL/pgSQL approach can be CPU-intensive at scale and recommends modern extensions like pgvector with HNSW or IVFFlat indexing for production workloads.