MongoDB Resources

Explore MongoDB's powerful integrations with AWS and key AI partners like LangChain, offering joint solutions to tackle today's most complex challenges. Learn how to leverage MongoDB's AI Application Program to build intelligent applications that drive real-world impact. Using MongoDB Atlas through AWS Marketplace simplifies the deployment process by offering streamlined billing, seamless integration with AWS services, and automated infrastructure management, allowing developers to focus more on building applications rather than managing databases.

• MongoDB Atlas in AWS Marketplace

• How to link your MongoDB and AWS Marketplace account

• MongoDB AI Applications Program

• MongoDB and AWS Partnership

Technical Tutorials for MongoDB Atlas on AWS for Generative AI

Dive into hands-on tutorials designed to help you implement MongoDB Atlas alongside AWS Bedrock, Amazon SageMaker, AWS Lambda, and AWS API Gateway to power scalable AI-driven applications. These guides will walk you through setting up, configuring, and optimizing your MongoDB Atlas instance to work seamlessly with AWS integration foundational models. Unlock the potential of combining managed cloud services for enhanced AI application performance.

• MongoDB With Bedrock Agent: Quick Tutorial

• MongoDB Atlas Vector Search and AWS Bedrock Modules RAG Tutorial 

• Part #1: Build Your Own Vector Search with MongoDB Atlas and Amazon SageMaker 

• Part #2: Create Your Model Endpoint With Amazon SageMaker, AWS Lambda, and AWS API Gateway | MongoDB 

• Part #3: Semantically Search Your Data With MongoDB Atlas Vector Search    

• Build Your Own Vector Search with MongoDB Atlas and Amazon SageMaker 

• Unlocking AI Potential with AWS | MongoDB 

• AWS and Generative AI - Services, Deployments and RAG with Bedrock | MongoDB   

LangChain Resources

Master LangChain, an innovative framework that connects language models to applications, by exploring step-by-step technical tutorials. These resources will guide you in building conversational AI tools, integrating with various data sources, and fine-tuning models for real-world use cases. Perfect for developers aiming to create intelligent and interactive applications using LangChain.

• LangChain Academy

• LangChain YouTube

• LangChain Docs (Python, JS)

• LangSmith Docs

• LangGraph Docs (Python, JS)

MongoDB Vector Search Resources

Discover the full potential of MongoDB Vector Search through a curated list of articles, guides, and case studies. Learn how to harness this cutting-edge feature to perform high-speed searches on unstructured data, enabling AI applications to deliver more relevant results. These resources will help you understand the practical applications and optimization techniques for vector search.

• MongoDB Atlas Vector Search 

• What are Vector Databases? 

• Atlas Vector Search Quickstart

• Atlas Vector Search Overview

• How to run vector search queries

AWS Bedrock Resources

Further detail on AWS Bedrock: Explore AWS Bedrock through in-depth resources that cover its foundational models, architecture, and integration with AWS services. Learn how to deploy generative AI models, scale them across your applications, and leverage Bedrock’s capabilities for custom AI development. Perfect for developers looking to accelerate AI deployment on the AWS cloud platform.

• AWS Bedrock

• AWS Bedrock User Guide

• Claude 3.5 Sonnet (Amazon Bedrock Edition)

• Integrating Foundation Models into Your Code with Amazon Bedrock