An organization is deploying a RAG application with Oracle AI Vector Search. They need to ensure that the vector index supports low-latency queries and can handle updates to the underlying documents (inserts, deletes, modifications) without significant performance degradation. Which two index features should they consider? (Choose TWO.)
IVF indexes can be rebuilt periodically to handle updates; with proper maintenance, they can provide low-latency queries.
Why this answer
An IVF (Inverted File) index with periodic rebuilds is well-suited for RAG applications that experience frequent updates (inserts, deletes, modifications). IVF indexes are designed for approximate nearest neighbor search, offering low-latency queries, but they can degrade over time as data changes; periodic rebuilds restore performance without requiring a full re-index of the entire dataset. This approach balances query speed with update tolerance, making it a practical choice for dynamic document collections in Oracle AI Vector Search.
Exam trap
The 1Z0-1127 exam often tests the misconception that HNSW indexes are always superior for dynamic workloads, but the question explicitly asks for two features that support low-latency queries and handle updates, and both IVF with periodic rebuilds and HNSW are valid; the trap is that candidates might overlook the periodic rebuild requirement for IVF or incorrectly assume HNSW is the only option, leading them to select only one correct answer or to dismiss IVF entirely.