Work out vector storage cost instantly with clear inputs, formula shown and shareable results.
Vector storage cost is payload plus index overhead, replicated. A 768-dimensional fp32 vector is 3,072 bytes and an HNSW graph adds roughly 30 percent for neighbour lists, so plan on about 4 KB per vector per replica. Because managed vector databases price on provisioned memory rather than disk, this is usually the dominant recurring line item in a RAG system.
Vector storage cost
bytes per vector = dimensions x 4 x 1.3; GB = vectors x bytes x replicas / 1e9; monthly = GB x price per GB-month
Quantise to int8 or use product quantisation, reduce dimensions with a Matryoshka-capable model, and archive cold partitions to a disk-backed tier.
For production availability yes, since a single node loses the index on failure and rebuilding takes time proportional to corpus size.