RAG Architectures Compared (Part 1): Naive, Advanced, and Modular RAG

📰 Medium · Machine Learning

Learn the differences between Naive, Advanced, and Modular RAG architectures and how to apply them in machine learning projects

intermediate Published 17 Apr 2026

Action Steps

Read the article to understand the basics of Naive RAG architecture
Compare the advantages and disadvantages of Advanced RAG architecture
Apply Modular RAG architecture to a project to improve scalability
Evaluate the performance of different RAG architectures using metrics such as accuracy and F1-score
Implement a RAG architecture in a machine learning framework such as PyTorch or TensorFlow

Who Needs to Know This

Machine learning engineers and researchers can benefit from understanding RAG architectures to improve their model's performance and efficiency

Key Insight

💡 Understanding the trade-offs between different RAG architectures is crucial for building efficient and effective machine learning models