Category: Announcements

In this post we are announcing the strengthening of the partnership between AWS and InfluxData as Timestream adopts InfluxDB as the main purpose-built time series database.

Amazon Neptune version 1.4.5 introduces engine improvements and support for AWS Graviton-based r8g instances. In this post, we show you how these updates can improve your graph database performance and reduce costs. We walk you through the benchmark results for Gremlin and openCypher comparing Neptune v1.4.5 on r8g instances against previous versions. You’ll see performance improvements of up to 4.7x for write throughput and 3.7x for read throughput, along with the cost implications.

Today, we’re announcing improved observability for throttled requests in Amazon DynamoDB. These enhancements provide developers with enriched exception messages, detailed Amazon CloudWatch metrics, and a new, more cost-effective mode for CloudWatch Contributor Insights. Together, these improvements make it straightforward to understand, monitor, and optimize your DynamoDB applications’ performance. In this post, we explore how these […]

Today, Amazon DocumentDB (with MongoDB compatibility) announced that Amazon DocumentDB version 3.6 will reach end of life on March 30, 2026. Starting March 31, 2026, you can continue to run Amazon DocumentDB version 3.6 on Extended Support. Extended Support provides fixes for critical security issues and bugs through patch releases for three years beyond the end of standard support of Amazon DocumentDB version 3.6.

Amazon ElastiCache now offers Extended Support so that you can upgrade to a new major version at a pace that meets your business requirements. Extended Support is a paid offering that provides critical security updates, bug fixes, and continued support for ElastiCache versions 4 and 5 for Redis OSS through January 31, 2029. Starting on February 1, 2026, ElastiCache Redis OSS v4 and v5 clusters that haven’t been upgraded will be automatically enrolled in Extended Support to provide continuous availability and security. In this post, we discuss what ElastiCache Extended Support entails, its key benefits, and the upgrade options available.

In April 2024, AWS announced support for Valkey, a community-driven fork of Redis born out of a shared belief that critical infrastructure software should be vendor neutral and open source. In this post, we share how, just over a year in, we remain fully committed to the Valkey project and announce support for the latest version with Amazon ElastiCache version 8.1 for Valkey. We explore the benefits of Valkey through real-world examples the benefits of the latest innovations, including a new hash table with additional memory efficiencies, support for Bloom filters, observability enhancements, and new functionality.

Amazon ElastiCache now supports Bloom filters: a fast, memory-efficient, probabilistic data structure that lets you quickly insert items and check whether items exist. In this post, we discuss two real-world use cases demonstrating how Bloom filters work in ElastiCache, the best-practices to implement, and how you can save at least 90% in memory and cost compared to alternative implementations. Bloom filters are available in ElastiCache version 8.1 for Valkey in all AWS Regions and at no additional cost.

AWS recently announced, in partnership with Google Cloud and the Valkey community, the general availability of Valkey General Language Independent Driver for the Enterprise (GLIDE) 2.0, the latest release. Valkey GLIDE is multi-language client library designed for reliability and performance. In this post, we discuss what Valkey GLIDE is and its key benefits, and then dive into its new enhancements.

Amazon Aurora, Amazon DynamoDB, and Amazon ElastiCache are popular choices for developers powering critical workloads, including global commerce platforms, financial systems, and real-time analytics applications. To enhance productivity, developers are supplementing everyday tasks with AI-assisted tools that understand context, suggest improvements, and help reason through system configurations. Model Context Protocol (MCP) is at the helm of this revolution, rapidly transforming how developers integrate AI assistants into their development pipelines. In this post, we explore the core concepts behind MCP and demonstrate how new AWS MCP servers can accelerate your database development through natural language prompts.

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse allows you to run analytics workloads on your DynamoDB data without having to set up and manage extract, transform, and load (ETL) pipelines. In this post we cover setting up Amazon SageMaker Unified Studio, followed by running data analysis to showcase its capabilities. We illustrate our solution walkthrough with an example of a credit card company that wants to analyze its customer behavior and spending trends.