AWS Database Blog

Category: Announcements

Announcing Valkey GLIDE 2.0 with support for Go, OpenTelemetry, and batching

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.

Supercharging AWS database development with AWS MCP servers

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 – Part 2

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.

Amazon DynamoDB zero-ETL integration with Amazon SageMaker Lakehouse – Part 1

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 two-part series, we first walk through the prerequisites and initial setup for the zero-ETL integration. In Part 2, 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.

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 […]

Prevent transaction ID wraparound by using postgres_get_av_diag() for monitoring autovacuum

In this post, we introduce postgres_get_av_diag(), a new function available in RDS for PostgreSQL to monitor aggressive autovacuum blockers. By using this function, you can identify and address performance and availability risks through actionable insights provided by postgres_get_av_diag().

New – Accelerate database modernization with generative AI using AWS Database Migration Service Schema Conversion

Today, we’re excited to inform you about a new generative AI feature in DMS SC. You can now use advanced language models to streamline and enhance your migration workflow. In this post, we discuss the key capabilities of DMS SC with generative AI and how to enable it to offer you additional recommendations to reduce manual conversion effort and time.

Introducing Amazon Aurora DSQL

Today, we introduce Amazon Aurora DSQL, the fastest serverless distributed SQL database for always available applications. It offers virtually unlimited scale, highest availability, and zero infrastructure management. It can scale to meet any workload demand without database sharding or instance upgrades. In this post, we discuss the benefits of Aurora DSQL and how to get started.

Amazon ElastiCache version 8.0 for Valkey brings faster scaling and improved memory efficiency

Today, we are adding support for Valkey 8.0 on Amazon ElastiCache. ElastiCache version 8.0 for Valkey brings faster scaling for ElastiCache Serverless and memory optimizations for node-based clusters. In this post, we discuss these improvements and how you can benefit from them.