Category: Amazon DynamoDB

Amazon DynamoDB is a serverless, NoSQL, fully managed database service that delivers single-digit millisecond latency at any scale. AWS recently announced the limited preview of attribute-based access control (ABAC) for Amazon DynamoDB. ABAC is an authorization strategy that defines permissions based on attributes. In AWS, these attributes are called tags. You can attach tags to […]

Amazon DynamoDB continuously sends metrics about its behavior to Amazon CloudWatch. Something I’ve heard customers ask for is how to get a count of successful requests of each operation type (for example, how many GetItem or DeleteItem calls were made) in order to better understand usage and costs. In this post, I show you how to retrieve this metric.

In this post, we explore how to transition from using Rockset to OpenSearch Service for your DynamoDB use-case effectively. To illustrate this integration, we consider a real-world example of a gaming company that tracks user interactions, such as in-game purchases and player scores, using DynamoDB. This data needs to be analyzed in real time to provide insights into user behavior, detect anomalies, and personalize the gaming experience.

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.

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.

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.

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.

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.

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, […]

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, […]