In order to fully utilize computer vision technology in retail stores, we present the United Retail Datasets (Unitail), an extensive large-scale benchmark of basic visual tasks on products that challenge algorithms for detecting, reading, and matching. The Unitail includes 1.8M quadrilateral-shaped instances annotated to improve product detection and offers a gallery-style OCR dataset comprising 1454 product categories, 30k text regions, and 21k transcriptions to enable reliable text recognition of products and encourage advanced product matching. In addition to evaluating the datasets using different state-of-the-art methods, we have developed a customized product detection model and a straightforward OCR-based matching solution, both of which demonstrate their effectiveness.