AWS Database Blog
Category: Amazon DynamoDB
Build scalable, event-driven architectures with Amazon DynamoDB and AWS Lambda
By combining DynamoDB streams with Lambda, you can build responsive, scalable, and cost-effective systems that automatically react to data changes in real time. In this post, we explore best practices for architecting event-driven systems using DynamoDB and Lambda. DynamoDB provides two options for capturing data changes (CDC): DynamoDB streams and Amazon Kinesis Data Streams (KDS). In this post, we focus exclusively on DynamoDB streams.
Building a GDPR compliance solution with Amazon DynamoDB
In this post, AWS Service Sector Industry Solutions shares our journey in developing a feature that enables customers to efficiently locate and delete personal data upon request, helping them meet GDPR compliance requirements. The mission of the Service Sector Solutions Engineering Team is to accelerate AWS Cloud adoption across diverse industries, including Travel, Hospitality, Gaming, and Entertainment. We work with customers from Cruise Lines, Lodging, Alternative Accommodation, Travel Agencies, Airports, Airlines, Restaurants, Catering, Casinos, Lotteries, and more.
Know before you go: Amazon DynamoDB sessions at AWS re:Invent 2024
It’s November, which means that AWS re:Invent 2024 is just around the corner! We’ve summarized a list of re:Invent sessions that include Amazon DynamoDB. We encourage readers who are interested in learning more about DynamoDB to bookmark this list to streamline how you schedule your conference week in Las Vegas this year.
How Channel Corporation modernized their architecture with Amazon DynamoDB, Part 2: Streams
Channel Corporation is a B2B software as a service (SaaS) startup that operates the all-in-one artificial intelligence (AI) messenger Channel Talk. In Part 1 of this series, we introduced our motivation for NoSQL adoption, technical problems with business growth, and considerations for migration from PostgreSQL to Amazon DynamoDB. In this post, we share our experience integrating with other services to solve areas that couldn’t be addressed with DynamoDB alone.
How Channel Corporation modernized their architecture with Amazon DynamoDB, Part 1: Motivation and approaches
Channel Corporation is a B2B software as a service (SaaS) startup that operates the all-in-one artificial intelligence (AI) messenger Channel Talk. This two-part blog series starts by presenting the motivation and considerations for migrating from RDBMS to NoSQL. In this post, we discuss the motivation behind Channel Corporation’s architecture modernization with Amazon DynamoDB, the reason behind choosing DynamoDB, and the four major considerations before migrating from Amazon Relational Database Service (Amazon RDS) for PostgreSQL.
Amazon DynamoDB data models for generative AI chatbots
Amazon DynamoDB is ideal for storing chat history and metadata due to its scalability and low latency. DynamoDB can efficiently store chat history, allowing quick access to past interactions. User-specific metadata, such as preferences and session information, can be stored to personalize responses and manage active sessions, enhancing the overall chatbot experience.In this post, we explore how to design an optimal schema for chatbots, whether you’re building a small proof of concept application or deploying a large-scale production system.
Build a scalable, context-aware chatbot with Amazon DynamoDB, Amazon Bedrock, and LangChain
Amazon DynamoDB, Amazon Bedrock, and LangChain can provide a powerful combination for building robust, context-aware chatbots. In this post, we explore how to use LangChain with DynamoDB to manage conversation history and integrate it with Amazon Bedrock to deliver intelligent, contextually aware responses. We break down the concepts behind the DynamoDB chat connector in LangChain, discuss the advantages of this approach, and guide you through the essential steps to implement it in your own chatbot.
What version of Amazon DynamoDB are you running?
Whether you’ve used DynamoDB for a day or a decade, this question has no practical relevance. As a serverless database, DynamoDB doesn’t have a version. DynamoDB has had no version upgrades, no maintenance windows, no patching, and no downtime due to maintenance since launching in January 2012. You access new DynamoDB features as they become […]
Import personalized recommendations from Amazon Personalize into Amazon DynamoDB
In this post, we explore how to import pre-generated Amazon Personalize recommendations into Amazon DynamoDB.
Vector search for Amazon DynamoDB with zero ETL for Amazon OpenSearch Service
As organizations increasingly rely on Amazon DynamoDB for their operational database needs, the demand for advanced data insights and enhanced search capabilities continues to grow. Leveraging the power of Amazon OpenSearch Service and Amazon Bedrock, you can now unlock generative artificial intelligence (AI) capabilities for your DynamoDB data. In this post, we show how you […]