AWS Database Blog

In this post, we show how you can use the Database Modernizer workshop to accelerate your database modernization journey from MySQL to Amazon DynamoDB. Traditional approaches to migrating from relational databases to NoSQL solutions like DynamoDB can take several months, requiring extensive expertise in data modeling, application refactoring, and migration strategies. The Database Modernizer workshop, which can be scheduled by your account team as part of the Amazon DynamoDB Immersion Day program, uses AI to help you complete database modernization projects in days instead of months.

In this post, we show an algorithm to efficiently compare two Amazon DynamoDB tables and find the differences between their items. We provide an example where two tables, each containing approximately half a billion items, are compared in less than 7 minutes, for less than $10.

Today, we’re introducing Amazon RDS Blue/Green support for Aurora Global Database, enabling database upgrades and modifications with minimal downtime. With just a few steps, you can create a blue/green deployment that establishes a fully managed staging (green) environment mirroring the existing production (blue) environment, including the primary and its associated secondary regions of the Global Database.

Part 1 of this series showed how to rate-limit calls to Amazon DynamoDB by using Python Boto3 event hooks. In this post, I expand on the concept and show how to rate-limit calls in a distributed environment, where you want a maximum allowed rate across the full set of clients but can’t use direct client-to-client communication.

In this post, I present a technique where a Python script making calls to Amazon DynamoDB can rate limit its consumption of read and write capacity units. The technique uses Boto3 event hooks to apply the rate limiting without having to modify the client code performing the read and write calls.

In this post, we explore the use cases for delayed replication, the recovery procedures, and best practices for managing delayed replicas to help ensure your database recovery strategy is both robust and efficient.

On Oct 28, 2025, Amazon DocumentDB (with MongoDB compatibility) introduced a new query planner (NQP) to improve database performance and stability. The redesigned architecture uses improved cost estimation techniques and optimized algorithms for smarter query plan selection.

Today, we are announcing Amazon Keyspaces (for Apache Cassandra) support for logged batches, a powerful feature that brings atomic, all-or-nothing write operations to your Apache Cassandra-compatible workloads. In this post, we explore the benefits of logged batches, demonstrate how to set up and run them, and discuss important considerations when using logged batches with Amazon Keyspaces.

Alight Solutions is a leading cloud-based human capital technology and services provider that has focused its operations on integrated benefits administration, healthcare navigation, and employee experience solutions. In this post, we share how Alight Solutions transformed their caching infrastructure using ElastiCache while maintaining strict performance requirements, achieving over 60% cost reduction, 70-80% reduction in operational overhead, migration of gigabytes of data with sub-0.5 millisecond performance for millions of users, and a 99.99% reduction in incident rate.

In this post, you will learn to migrate a regional Amazon DocumentDB cluster from one AWS Region to another using the Global Cluster feature with low downtime and without performance impact.