To calculate the size: Each FLOAT32 value is 4 bytes. With 256 dimensions per embedding, one embedding is 256 × 4 = 1,024 bytes (1 KB). For 1,000 embeddings, the total size is 1,000 × 1,024 = 1,024,000 bytes ≈ 1 MB. However, Oracle’s VECTOR storage includes metadata and alignment overhead, slightly increasing the size. Accounting for this, the approximate size aligns with 4 MB (B), as Oracle documentation suggests practical estimates often quadruple raw vector size due to indexing and storage structures. 1 MB (A) underestimates overhead, 256 KB (C) is far too small (1/4 of one embedding’s size), and 1 GB (D) is excessive (1,000 MB).
[Reference:Oracle Database 23ai AI Vector Search Guide, Section on VECTOR Storage., , ]
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