Catalog listing Microsoft Learn module

Get started with generative AI in Azure Database for PostgreSQL: Review

Item: Get started with generative AI in Azure Database for PostgreSQL
Rating: 2.5
Author: Priya S.

Named reviewer score 2.5 / 5

Teaching 2.0
Hands-on 3.0
Freshness 3.5
Value 3.0
Career fit 2.0

Reviewed by Priya S. Data scientist at a mid-sized SaaS company

Provider: Microsoft Learn Format: Self-paced module Time: About an hour Price: Free on Microsoft Learn — check current pricing if a credential exam is attached

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Reviewer's verdict

This is a quick feature demo for the `azure_ai` extension inside a PostgreSQL database, not a course on generative AI. Treat it as a 30-minute interactive product page.

Decision summary

2.5/5 Last verified: August 31, 2026

Best for

DBAs or PostgreSQL developers curious about the `azure_ai` extension's basic syntax.

Watch for

Extremely shallow; it's a feature tour, not a tutorial on building anything.

Teaching 2.0
Hands-on 3.0
Freshness 3.5
Value 3.0
Career fit 2.0

Who it's for

DBAs or PostgreSQL developers curious about the `azure_ai` extension's basic syntax.

Who should skip it

Anyone looking for a conceptual understanding of generative AI or RAG.

Pros

Provides a quick, copy-paste overview of the `azure_ai` extension.
The sandbox environment is pre-configured, saving setup time.
Introduces several related Azure schemas (AI, Cognitive, ML) in one place.

Cons

Extremely shallow; it's a feature tour, not a tutorial on building anything.
Confuses the roles of embedding models and generation models in its explanations.
The exercise is just running pre-written queries without explaining the 'why'.

Running `SELECT azure_ai.generate_text('What is the capital of France?');` inside a pre-configured sandbox is basically the entire hands-on part. You just copy-paste some SQL to call an Azure OpenAI endpoint for embeddings and completions. That's it. It’s a quick tour of the function signatures. The text tries to explain what's happening but gets the details fuzzy, particularly around the roles of embedding versus completion models. It feels like it was written to tick a box for 'GenAI'.

There's no discussion of vector indexing strategies (pgvector is just there?), chunking, or even basic prompt engineering. The module shows you that `azure_ai.generate_text()` and `azure_ai.create_embeddings()` exist. For a data scientist, it's pretty useless. For a Postgres developer who just needs the function syntax, maybe it saves ten minutes of reading the official docs. It's a product brief, not a proper lesson.

Last verified: August 31, 2026. We re-check course details periodically — see our methodology. Pricing and availability can change; always confirm on the official site.

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