A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings…

The correct answer is B. Amazon Aurora PostgreSQL. The requirement is to identify an AWS database service that supports the storage and querying of embeddings (from a generative AI model) as vectors. Embeddings are typically high-dimensional numerical representations of data (e.g., text, images) used in AI applications like…

Submitted by saadiq_pk· Mar 30, 2026Data Engineering for Machine Learning

Question

A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings from a generative AI model as vectors in the database. Which AWS service will meet these requirements?

Options

AAmazon Athena
BAmazon Aurora PostgreSQL
CAmazon Redshift
DAmazon EMR

How the community answered

(65 responses)

A
6% (4)
B
83% (54)
C
9% (6)
D
2% (1)

Explanation

The requirement is to identify an AWS database service that supports the storage and querying of embeddings (from a generative AI model) as vectors. Embeddings are typically high-dimensional numerical representations of data (e.g., text, images) used in AI applications like conversational search. The database must support vector storage and efficient vector similarity searches. Amazon Aurora PostgreSQL- Compatible Edition supports the pgvector extension, which enables efficient storage and similarity searches for vector embeddings. This makes it suitable for AI/ML workloads such as natural language processing and recommendation systems that rely on vector

Topics

#Vector database#Generative AI embeddings#Aurora PostgreSQL#pgvector

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