# Six RAG strategies, explained simply (with code).

DevFeed: [Six RAG strategies, explained simply (with code).](<https://devfeed.tech/articles/six-rag-strategies-explained-simply-with-code-18321.md>)

Original publisher: [Read original article](<https://newsletter.aiengineer.co/p/six-rag-strategies-explained-simply>)

Author: Owain Lewis

Published: 2026-04-03T08:36:55Z

Content type: tutorial

Language: en

Sources: [The AI Engineer](<https://devfeed.tech/sources/the-ai-engineer.md>)

Topics: [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Database](<https://devfeed.tech/topics/database.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [database](<https://devfeed.tech/tags/database.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [full-text-search](<https://devfeed.tech/tags/full-text-search.md>), [rag](<https://devfeed.tech/tags/rag.md>), [retrieval](<https://devfeed.tech/tags/retrieval.md>), [tutorials](<https://devfeed.tech/tags/tutorials.md>), [vector-search](<https://devfeed.tech/tags/vector-search.md>)

## AI overview

This tutorial explains retrieval-augmented generation and compares retrieval strategies, including loading complete documents, full-text search, and vector search. It presents Postgres as a practical option for implementing these approaches and discusses their trade-offs.

## Source excerpt

Six Ways to Retrieve Data for an LLM