Core Concepts
ベクトルデータ管理における効率的なアクセスパスの重要性と、混合ベクトル-リレーショナル検索における最適な戦略の検討。
Stats
Vector indexes aim to reduce search across all embeddings based on construction-time parameters.
Tensor-based computation is more cache-efficient, keeping data in caches for efficient processing.
HNSW algorithm provides an approximate nearest neighbor search capability with tunable recall and speed properties.
Quotes
"Indexes represent a probe-based approach, facing the penalty of random accesses and less-suitable relational filtering."
"Vector indexes perform better when more tuples satisfy the selection condition."