Category: Announcements

Today, we are excited to announce the general availability of Amazon Aurora MySQL 8.4, our latest major version, compatible with community MySQL 8.4.7. This release marks an important milestone for Aurora MySQL customers, introducing a simplified versioning model aligned directly with community MySQL, along with a streamlined patch version experience, and the full set of community MySQL 8.4 enhancements. In this post, we discuss the customer challenges that this release addresses, introduce Aurora MySQL 8.4, walk through the new versioning approach and its benefits for customers, cover the key capabilities delivered in Aurora MySQL 8.4, and show you how to get started.

In this post, we share the version currency timelines for Aurora and RDS open source engines. We also explain why timelines differ across engines and how you can use them to plan your upgrades.

Today, we are announcing ExtendDB, an open source Amazon DynamoDB-compatible adapter with pluggable storage backends, released under the Apache 2.0 License. ExtendDB implements the DynamoDB wire protocol and ships with PostgreSQL as its first backend, so any AWS SDK, CLI, or tool that works with DynamoDB works with ExtendDB unchanged. In this post, we introduce ExtendDB, walk through getting started, and explain the architecture. This is a v0.1 release for development, testing, and experimentation.

In this post, we demonstrate how to configure Aurora DSQL Change Data Capture and stream database changes into Kinesis Data Streams. You will learn how CDC works, how to configure a streaming pipeline, and how to consume change events. By the end of this post, you will have a working CDC pipeline that streams database changes into a durable event stream that downstream applications can process.

Amazon ElastiCache now supports Valkey 9.0. This brings the latest community-driven innovations from the Valkey open source project to address the performance and capability requirements of applications as they grow more data-intensive and latency-sensitive, such as real-time analytics, AI-driven retrieval, and high-throughput caching. In this post, we explore how these enhancements help customers build faster applications, streamline architectures, and support new real-time and AI-driven workloads.

New search capabilities are available in ElastiCache version 9.0 for Valkey. In this post, we walk through the new search capabilities, show how they work together, and build a search and recommendation engine from scratch.

Amazon ElastiCache now supports aggregation queries, so you can filter, group, transform, and summarize data directly in your cache with a single query. This post walks through the use cases that aggregations unlock, and shows how they work by building a faceted browsing engine using Amazon ElastiCache for Valkey.

Two years ago, Valkey emerged as a community-driven response to the need for a truly open, vendor-neutral alternative to Redis. In this post, we’ll look back at two years of progress, highlighting the rapid adoption of Valkey, the innovations delivered by the community, and what these developments mean for the future of modern caching and […]

This technical deep dive into Amazon Timestream for InfluxDB 3 explores the architectural decisions, features, and capabilities that make this release a significant evolution in time series database technology. This next-generation time series database represents is an architectural redesign from the previous engine version; built from the ground up with modern technologies including Rust for core performance, Apache Arrow for columnar data processing, Apache Parquet for efficient storage, and Apache Arrow Flight SQL for high-performance querying.

Amazon Aurora Serverless is an on-demand, auto scaling configuration for Aurora that scales up to support your most demanding workloads and down to zero when you don’t need it. The latest improvements deliver up to 30% better performance and enhanced scaling that understands your workload. These enhancements are available at no additional cost for a better price-performance ratio. In this post, we’ll share recent performance and scaling improvements with benchmark results, showing how Aurora Serverless can now scale up to 45.0% faster with a 32.9% faster workload completion time.