AWS Database Blog

Jason Hunter

Author: Jason Hunter

Announcing configurable point-in-time recovery periods for Amazon DynamoDB

Amazon DynamoDB enables you to back up your table data continuously by using point-in-time recovery (PITR). When you enable PITR, DynamoDB backs up your table data automatically with per-second granularity. PITR helps protect you against accidental writes and deletes. For example, if a test script accidentally writes to a production DynamoDB table, or someone mistakenly […]

Monitor Amazon DynamoDB operation counts with Amazon CloudWatch

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.

Use Amazon DynamoDB incremental export to update Apache Iceberg tables

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB recently launched a new feature: Incremental export to Amazon Simple Storage Service (Amazon S3). You can use incremental exports to update your downstream systems regularly using only the changed data. You no longer need to do a […]

Introducing incremental export from Amazon DynamoDB to Amazon S3

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It’s a fully managed, multi-Region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. In 2020, DynamoDB introduced a feature to export DynamoDB table data to Amazon Simple Storage Service (Amazon S3) with […]

Handle traffic spikes with Amazon DynamoDB provisioned capacity

If you’re using Amazon DynamoDB tables with provisioned capacity, one challenge you might face is how best to handle a sudden request traffic increase (spike) without being throttled. The more sudden and extended the traffic spike, the more likely a table will experience throttles. However, throttles aren’t inevitable even for spiky traffic. Here we walk you through eight designs to handle traffic spikes, and present their advantages and disadvantages.

Generate a distinct set of partition keys for an Amazon DynamoDB table efficiently

Amazon DynamoDB is a fully managed, serverless NoSQL database service that provides fast and predictable performance with seamless scalability. Every table in DynamoDB has a schema which specifies if it has a simple partition key (for pure key-value lookups), or a partition key and sort key both (for more complex query patterns). You use these […]

Cost-effective bulk processing with Amazon DynamoDB

January 2025: The calculations in this post have been updated following DynamoDB’s 50% reduction in on-demand throughput pricing. Refer to New – Amazon DynamoDB lowers pricing for on-demand throughput and global tables to learn more. Your Amazon DynamoDB table might store millions, billions, or even trillions of items. If you ever need to perform a […]

How to use Amazon CloudWatch to monitor Amazon DynamoDB table size and item count metrics

Amazon DynamoDB sends metrics about its operations to Amazon CloudWatch. At the time of this writing, the list includes 33 metrics including: throughput consumed and provisioned, account and table limits, request latencies, system errors, and user errors. Two metrics not included are the DynamoDB table size and item count. These values can be observed in […]

Implement resource counters with Amazon DynamoDB

When developing applications, you often need to implement a counter to accurately track actions such as votes cast, the available quantity of a resource in an eCommerce store, or tickets available for an event. These counters must be updated as the resource quantity changes. In this post, we explore seven approaches to implementing resource counters […]