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AI0-001 AI Infrastructure and Technologies Practice Question

An organization is building a recommendation system that requires low-latency vector similarity search. They need to store and query millions of embeddings. Which THREE technologies are appropriate for this task?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Weaviate

Pinecone, Weaviate, and pgvector are vector databases designed for similarity search. Snowflake and S3 are not optimized for vector search.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Snowflake
Why it's wrong here
Snowflake is a data warehouse, not designed for vector similarity search.
✗
Amazon S3
Why it's wrong here
S3 is object storage, not a search engine.
✓
Weaviate
Why this is correct
Weaviate is an open-source vector database with built-in similarity search.
✓
pgvector
Why this is correct
pgvector adds vector similarity search to PostgreSQL.
✓
Pinecone
Why this is correct
Pinecone is a managed vector database with high-performance similarity search.

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

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This AI0-001 question is part of Courseiva's 754-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

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