Category: Technical How-to

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.

This is a guest blog by Arthur Bigeard, Founder at gdotv, in partnership with Charles Ivie, Sr Graph Architect at AWS. G.V() is a graph database IDE available for Desktop or on AWS Marketplace, offering extensive graph visualization and querying capabilities for Amazon Neptune and Neptune Analytics. In Part 1 of this series, we demonstrated […]

This is a guest blog post by Richard Loveday, Head of Product at Graph.Build, in partnership with Charles Ivie, Graph Architect at AWS. The Graph.Build platform is a dedicated, no-code graph model design studio and build factory, available on AWS Marketplace. Knowledge graphs have been widely adopted by organizations, powering use cases such as social […]

In this post, we walk through how we used Kiro, an agentic Integrated Development Environment (IDE), to build a complete fitness center management application that digitizes paper-based fitness tracking. We explore Kiro’s spec-driven development workflow and see how it transforms complex application development into a streamlined, iterative process. Our solution uses Amazon DocumentDB as the backend.

Amazon RDS for SQL Server now supports the Optimize CPU feature. With the Optimize CPU feature you can define the number of vCPUs when you launch new instances or when modifying existing database instances. This feature also provides a detailed billing breakdown of RDS infrastructure costs, and licensing costs for SQL Server and Windows OS. It is available starting from the 7th Generation instance class. In this post, we explore how to use the Optimize CPU feature with Amazon RDS for SQL Server.

This post shows how to build a semantic cache using vector search on Amazon ElastiCache for Valkey. As detailed in the Impact section of this post, our experiments with semantic caching reduced LLM inference cost by up to 86 percent and improved average end-to-end latency for queries by up to 88 percent.

In this post, we demonstrate how to set up a zero-ETL integration between self-managed databases such as MySQL, PostgreSQL, SQL Server, and Oracle to Amazon Redshift. The transactional data from the source gets replicated in near real time on the destination, which processes analytical queries.

In this post, I explore how Amazon Aurora DSQL uses Amazon Time Sync Service to build a hybrid logical clock solution.

Amazon Aurora DSQL employs an active-active distributed database design, wherein all database resources are peers and serve both write and read traffic within a Region and across Regions. This design facilitates synchronous data replication and automated zero data loss failover for single and multi-Region Aurora DSQL clusters. In this post, I discuss the individual components and the responsibilities of a multi-Region distributed database to provide an ACID-compliant, strongly consistent relational database.