Weaviate Product Quantization: Up to 90% Memory Reduction - Tradeoff in Recall

AI Impact Summary

Weaviate’s Product Quantization (PQ) technique offers up to 90% memory reduction by compressing vectors, but this comes with a significant trade-off: a drop in recall. The compression process replaces continuous vector coordinates with learned codes, effectively creating a quantized vector space where vectors within the same code region become indistinguishable, leading to reduced search accuracy. This requires a fallback mechanism to drill down into the full, uncompressed representation when needed, adding complexity to the search process.