RAG vs CAG: The New Era in Knowledge Processing

Introduction

In the world of artificial intelligence, knowledge retrieval and processing methods are constantly evolving. While Retrieval-Augmented Generation (RAG) systems have long been the standard, Cache-Augmented Generation (CAG) approaches are showing the potential to revolutionize this field.

How Traditional RAG Works

RAG systems operate on the principle of real-time data retrieval from external knowledge sources. For each query:

1. Database search is performed
2. Relevant documents are selected
3. Information is processed
4. Response is generated

https://www.superannotate.com/blog/rag-explained

Challenges Faced by RAG

• Repeated database queries for each request
• High latency (1.5–2 seconds)
• Complex system architecture and high maintenance costs
• Risk of inconsistency in document selection

https://www.analyticsvidhya.com/blog/2024/07/building-agentic-rag-systems-with-langgraph/

CAG: Next-Generation Knowledge Processing

CAG’s Innovative Approach