Category: Intermediate (200)

Amazon Relational Database Service (Amazon RDS) for SQL Server now offers the Optimize CPU feature, which enabled control over vCPU allocation through core count modification setting. SQL Server licensing costs can consume a significant portion of your database budget, especially when you’re paying for vCPUs that aren’t fully utilized. This post demonstrates how to implement the Optimize CPU feature to potentially reduce licensing costs while maintaining performance for both new and existing Amazon RDS instances, along with performance benchmarking results and cost implications.

As a global leader in the online travel industry, Booking.com continuously works to improve the travel experience for its users. Latency is a key factor in achieving this—nobody likes waiting for their search results to be returned. In this post, we share how Booking.com designed a well-architected Amazon ElastiCache-based feature platform, achieving ultra-low latency and high throughput, to ensure the best possible user experience.

In this post, we show you how to create and deploy SQL Server Developer Edition on Amazon RDS.

With the introduction of the additional storage volume feature, you can now attach up to three additional storage volumes to your Amazon RDS for SQL Server instances. By using this feature, you can distribute your data and log files across multiple volumes. This enhancement offers more granular control over storage configuration and performance optimization. In this post, you will learn about the following scenarios: Adding a new storage volume, Scaling an existing storage volume, Restoring a database on an additional storage volume, and Deleting a storage volume.

In this post, we show how you can turn your ideas into full-stack applications with Kiro powers for Aurora. We explore how a new innovation, Kiro powers, can help you use Amazon Aurora best practices built into your development workflow, automatically implementing configurations and optimizations that make sure your database layer is production-ready from day one.

Netflix operates a global streaming service that serves hundreds of millions of users through a distributed microservices architecture. In this post, we examine the technical and operational challenges encountered by their Online Data Stores (ODS) team with their current self-managed distributed PostgreSQL-compatible database, the evaluation criteria used to select a database solution, and why they chose to migrate to Amazon Aurora PostgreSQL to meet their current and future performance needs. The migration to Aurora PostgreSQL improved their database infrastructure, achieving up to 75% increase in performance and 28% cost savings across critical applications.

In this second post, I examine Aurora DSQL’s architecture and explain how its design decisions impact functionality—such as optimistic locking and PostgreSQL feature support—so you can assess compatibility with your applications. I provide a comprehensive overview of the underlying architecture, which is fully abstracted from the user.

Amazon DynamoDB has announced support for up to 8 attributes in composite keys for Global Secondary Indexes (GSIs). Now, you can specify up to four partition keys and four sort keys to identify items as part of a GSI, allowing you to query data at scale across multiple dimensions. In this post we show you how to design similar data models more efficiently using Global Secondary Indexes with the additional attribute support in composite keys and provide examples of DynamoDB data models with reduced complexity.

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.