Nyris & Qdrant: How Vectors are the Future of Visual Search - Qdrant

What this post added

This post details how Nyris, a visual search solutions provider, adopted Qdrant for their visual product search engine. It covers Nyris's journey from early SIFT features to CNN embeddings, their evaluation process for vector search engines (focusing on accuracy, speed, insert speed, TCO, data sovereignty, and Qdrant's specialization), and the specific benefits they derive from Qdrant in production (JWT security, scalability, flexible search, data handling, Rust implementation, cost-effectiveness). It also touches on Qdrant's quantization and integer8 support as key differentiators.