SAA-C03 Q296 · Database

Question

A company launches a new web application that uses an Amazon Aurora PostgreSQL database. The company wants to add new features to the application that rely on AI. The company requires vector storage capability to use AI tools. Which solution will meet this requirement MOST cost-effectively?

Accepted Answer

**Option D: Install the pgvector extension on the Aurora PostgreSQL database**

**Step-by-step reasoning:**

1. **Existing infrastructure reuse**: The company already has an Aurora PostgreSQL database running. The pgvector extension can be installed directly on this existing database — no new service provisioning required.

2. **Vector storage capability**: pgvector is a PostgreSQL extension that adds vector data types, vector indexing (IVFFlat, HNSW), and similarity search operators. This fully satisfies the requirement for vector storage to support AI tools.

3. **Cost-effectiveness**: This is the key differentiator. Installing an extension on an existing database incurs **zero additional infrastructure cost**. There's no need to provision, manage, or pay for a separate service. The vect

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🏗️ Architecture

⚙️ Operations

💰 Cost

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