In the current AI generation, where organizations deal with a vast inventory of images, identifying duplicates can be a daunting task. Distributed deduplication at scale is essential for optimizing storage, reducing redundancy, and maintaining data integrity. This article provides insight into the architectural design and practical implementation for deduplicating 100 million images efficiently using state-of-the-art tools and approaches.

Challenges in Image Deduplication

Scale

Processing millions or even billions of images demands: