Passing the Baton: High Throughput Distributed Disk-Based Vector Search with BatANN

BatANN system by Dang et al. for high-throughput distributed disk-based vector search. Supports scalable ANN in distributed environments.

CoTra system by Zhi et al. for efficient distributed vector search using RDMA. Published in SIGMOD 2026 proceedings.

Highly-efficient billion-scale approximate nearest neighbor search algorithm introduced by Chen et al. Focuses on scalability and performance for large datasets in high-dimensional spaces. Relevant for vector database indexing techniques.

VLDB 2023 paper proposing ARKGraph, a graph-based method for all-range approximate k-nearest neighbor search that adapts to various recall requirements.

SIGKDD 2022 paper introducing BLISS, a billion-scale indexing method using iterative re-partitioning for large-scale approximate nearest neighbor search.

TKDE 2024 paper presenting DIMS, a distributed indexing method for efficient similarity search across metric spaces. The approach enables parallel processing of vector similarity queries at scale.