This survey paper provides an overview of the landscape, technologies, and applications of vector databases, making it a valuable resource for understanding the field.

Benchmark results and tools by MyScale aimed at measuring the performance of vector databases in various search and retrieval tasks.

A curated directory of resources, tools, tutorials, and libraries dedicated to vector databases, focusing on efficient data retrieval, similarity search, and machine learning applications.

Efficient multi-vector retrieval system using sparsified late interaction with inverted indexes. Achieves 40% less storage and 83% lower latency than ColBERT-v2 while maintaining competitive accuracy.

Maze is a web-scale video deduplication system that relies on large-scale approximate nearest neighbor vector search over video embeddings to detect and remove duplicate or near-duplicate videos efficiently. While not a general-purpose vector database, it represents a specialized, production-scale application of vector search infrastructure for multimedia content management.

A research group focused on advancing the theory and practice of vector databases, providing resources, publications, and tools related to vector database technology.