Similarity Metric

The similarity metric is one of the core design decisions that directly affects retrieval quality in vector databases. Options such as cosine similarity, inner product, or Euclidean distance may behave differently depending on the embedding structure. Choosing the wrong metric can lead to weak retrieval even with strong embeddings. For that reason, similarity-metric selection must align with the modeling logic.