1Z0-184-25 Question 72
Single answerYou are designing an image cataloging application on Oracle Cloud Infrastructure. Each image is converted into embedding vectors that must be stored for fast, exact similarity searches in real time. You expect around 1 million images in the first phase, with the possibility of scaling to tens of millions as the application grows. Which approach best ensures accurate, exact similarity search performance for this vector data in OCI?
- A
Store vectors in Oracle Object Storage and use pre-signed URLs for direct retrieval of similar images.
- B
Use Oracle Database 23c or later with vector support and create an index optimized for exact similarity queries.
- C
Implement approximate nearest neighbor indexes through a custom engine running on Oracle Container Engine for Kubernetes (OKE).
- D
Store vectors as JSON documents in Oracle NoSQL Database without specialized indexing.
Show answer and explanation
Correct answer: B
Explanation
Exact similarity search in Oracle Cloud Infrastructure often relies on vector-enabled databases that provide native vector data types and indexing. Oracle Database 23c and later versions include specific features for vector similarity queries, allowing you to store, index, and search embedding vectors precisely. By using these capabilities, you can directly handle large vector datasets with consistent accuracy. Refer to the Oracle Database Advanced Analytics and Machine Learning documentation for further details on vector-based indexing and query optimization.
- A. Incorrect.
Incorrect. While Object Storage can hold your images, it does not provide built-in vector indexing or similarity search capabilities. You would still need a separate search engine to perform the exact similarity matching.
- B. Correct.
Correct. Oracle Database 23c (and later) provides native vector data types and specialized indexes that support exact similarity searches. This approach leverages Oracle Database� built-in capabilities for scalable indexing and querying, ensuring precise results at scale.
- C. Incorrect.
Incorrect. Approximate nearest neighbor (ANN) methods can be fast, but they focus on speed over precision. If your business requirement emphasizes exact matching, relying on ANN indexing alone is less accurate.
- D. Incorrect.
Incorrect. Oracle NoSQL Database is suitable for key-value or JSON documents, but it does not natively support specialized vector indexing for exact similarity searches, making queries potentially slow and complex for large-scale vector data.