This is an AWS community-driven repository packed with Amazon DynamoDB code samples, solutions, and SDK examples to empower your cloud-native development.
- Comprehensive examples covering popular programming languages
- Infrastructure as code templates for easy DynamoDB deployments
- Schema design patterns to optimize your data models
- Handy scripts and workshops to level up your DynamoDB skills
- Integration with cutting-edge AI technologies like Amazon Bedrock
- Click any language badge to explore examples.
- Each README includes setup instructions and use cases.
Explore the various folders and resources in this comprehensive DynamoDB repository:
- 🗃️ archived: This folder contains deprecated samples and code.
- 📂 examples: Includes sample scripts and integrations, with subfolders for each category, such as SDK examples.
- 🗁 infrastructure_as_code: Contains templates for deploying DynamoDB resources to AWS.
- 🗂 schema_design: A collection of schema design patterns for DynamoDB table implementations.
- 🗒️ scripts: Utility scripts for executing actions on your DynamoDB tables.
- 🗓️ workshops: Stores workshop content to help you learn DynamoDB in real-world scenarios.
Dive into this repository and unlock the power of integrating Amazon Bedrock's cutting-edge large language models (LLMs) with the scalable NoSQL capabilities of AWS DynamoDB. These comprehensive examples will guide you through building context-aware chatbots and sophisticated AI applications that can maintain seamless conversations across sessions.
These examples are designed to help developers, data scientists, and AI enthusiasts quickly get started with building sophisticated, cloud-native AI applications. By leveraging the power of Bedrock and DynamoDB, you can create scalable, context-aware solutions that push the boundaries of what's possible.
- 🔗 Bedrock Integration: Seamlessly connect to Amazon Bedrock and harness the latest LLM technologies from industry-leading providers like Anthropic and AI21 Labs.
- 💾 DynamoDB for Context Management: Leverage DynamoDB's NoSQL database to store and retrieve chat history, enabling your AI models to maintain context and deliver more coherent, relevant responses over time.
- 🚀 Scalable and Serverless Architecture: Build applications that are both scalable and cost-effective, with DynamoDB handling large-scale data storage and Bedrock providing robust AI capabilities without the need to manage underlying infrastructure.
- 🛠️ Real-world Examples: Explore practical examples that cover setting up the environment, creating DynamoDB tables, integrating with Bedrock, and building a fully functional web-based chatbot using Streamlit.
Explore the DynamoDB and Bedrock examples >>
This repository is a collaborative effort, and we welcome contributions from the community. Whether you have a new code sample, an optimization to an existing solution, or an idea for enhancing the project structure, we encourage you to get involved.
To contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your changes.
- Make your modifications and ensure they align with the project's guidelines.
- Submit a pull request, clearly describing the changes and their purpose.
Our team will review your contribution and provide feedback. Once approved, your changes will be merged into the main codebase, and you'll be credited as a contributor.
Special thanks to other contributors to this repo before it was moved over to this current location. Here are their GitHub users:
- @jprivillaso
- @tywalch
- @normj
- @jasonwadsworth
- @johanrin
- @DejanBelic
- @TLaue
This project exists thanks to all the people who contribute. Check out the full list of contributors to see who has helped so far.
Together, we can make this DynamoDB repository an even more valuable resource for the AWS community. 🚀
