AWS Database Blog

Category: Amazon DynamoDB

Key considerations when choosing a database for your generative AI applications

In this post, we explore the key factors to consider when selecting a database for your generative AI applications. We focus on high-level considerations and service characteristics that are relevant to fully managed databases with vector search capabilities currently available on AWS. We examine how these databases differ in terms of their behavior and performance, and provide guidance on how to make an informed decision based on your specific requirements.

Amazon DynamoDB use cases for media and entertainment customers

In this post, we discuss how Amazon DynamoDB helps media and entertainment customers overcome these challenges for streaming and media supply chain workloads. We also share customer examples, such as Disney, Warner Bros. Discovery, ViacomCBS, and other media applications that are built with DynamoDB.

How Scopely scaled “MONOPOLY GO!” for millions of players around the globe with Amazon DynamoDB

In this post, we show you how Amazon DynamoDB enabled Scopely to quickly respond to their rapid growth with consistent game performance and availability. We also describe how Scopely improved the availability and performance of their matchmaking service with DynamoDB after facing challenges at scale with other solutions.

Use Spring Cloud to capture Amazon DynamoDB changes through Amazon Kinesis Data Streams

In this post, we demonstrate how you can use Spring Cloud to interact with Amazon DynamoDB and capture table-level changes using Kinesis Data Streams through familiar Spring constructs. We run you through a basic implementation and configuration that will help you get started.

Use Amazon DynamoDB incremental exports to drive continuous data retention

Amazon DynamoDB supports incremental exports to Amazon Simple Storage Service (Amazon S3), which enables a variety of use cases for downstream data retention and consumption. In this post, we show you how to maintain a continuously updating export of your table data by doing a bootstrap full export followed by an ongoing series of incremental exports.

Choose the right change data capture strategy for your Amazon DynamoDB applications

Change data capture (CDC) is the process of capturing changes to data from a database and publishing them to an event stream, making the changes available for other systems to consume. Amazon DynamoDB CDC offers a powerful mechanism for capturing, processing, and reacting to data changes in near real time. Whether you’re building event-driven applications, […]

Enable fine-grained access control and observability for API operations in Amazon DynamoDB

Customers choose Amazon DynamoDB to improve their applications’ performance, scalability, and resiliency. DynamoDB’s serverless architecture simplifies operations by abstracting hardware, scaling, patches, and maintenances. Managing data access and security in DynamoDB is different than instance-based database solutions. DynamoDB uses AWS Identity and Access Management (IAM) to authenticate and authorize access to resources, whereas RBDMS solutions rely on firewalls rules, […]

Freecharge lowered their identity management system cost and improved scaling by switching to Amazon DynamoDB

Freecharge, subsidiary of Axis Bank, is a payment app serving over 100 million users across India. Over the years, Freecharge has transformed to become one of the leading financial services and investment apps in the country. Freecharge has always been known for offering safe and seamless UPI payments, utility bill payments, mobile/DTH recharges, and much […]

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud. Aurora combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open-source databases. Serverless technologies eliminate infrastructure management tasks […]

How Heroku reduced their operational overhead by migrating their 30 TB self-managed database from Amazon EC2 to Amazon DynamoDB

Heroku is a fully managed platform as a service (PaaS) solution that makes it straightforward for developers to deploy, operate, and scale applications on AWS. Founded in 2007 and a part of Salesforce since 2010, Heroku is the chosen platform for millions of applications—from development teams at small startups to large enterprises with large-scale deployments. […]