Case Study: Badger Technologies achieves 2.5x faster vector search with ApertureData ApertureDB

Badger Technologies Uses Aperturedb To Solve “wrong Product" Placement Problems At Scale

Badger Technologies, a retail automation company that uses multipurpose robots for smart shelf scanning, needed a faster and more stable way to search massive libraries of embeddings generated from thousands of store images per second. Their previous vector database solution was maxing out at around 4,000 queries per second and causing stability issues, which delayed reporting on out-of-stock, misplaced, and mispriced products.

ApertureData’s ApertureDB was implemented to power vector search, image, metadata, and embedding management in a single platform. With ApertureDB, Badger Technologies improved vector similarity search performance by 2.5x, increased throughput to over 10,000 queries per second in production, and saw even higher performance in lab and next-release testing, helping them scale deployments more reliably and setting them up for ML training dataset management.

Badger Technologies

Leslie Hensley

Solution Architect