Shounak Acharya

MongoDB

Sneha Das Gupta

Senior Partner Solutions Architect

This article compares five retrieval strategies namely pre-filtering, vector search, full-text search, hybrid search, and graph-based retrieval for RAG.

Depth-first Hybrid Search for GraphRAG

Prasad Pillalamarri

Discover how to leverage MongoDB for building powerful knowledge bases in RAG (Retrieval-Augmented Generation) architectures. This comprehensive guide explores using MongoDB's document model to construct relationship graphs, implement vector search, and create interactive visualizations. Learn step-by-step techniques for storing entities and relationships, querying graph structures, and generating dynamic network visualizations using d3.js. Perfect for developers looking to enhance their RAG systems with MongoDB's flexibility and performance. Includes code examples for creating collections, embedding hierarchical data, and optimizing queries for visualization rendering.

Shounak Acharya

Content by Shounak Acharya

Depth-first Hybrid Search for GraphRAG

Building a Knowledge Base and Visualization Graphs for RAG With MongoDB