AWS Database Blog

In this post, we explore how to use resource-based policies with DynamoDB Streams to enable cross-account Lambda consumption. We focus on a common pattern where application workloads live in isolated accounts, and stream processing happens in a centralized or analytics account.

The new aws_dynamodb_global_secondary_index resource treats each GSI as an independent resource with its own lifecycle management. You can use this feature to make capacity adjustments for GSI and tables outside of Terraform. In this post, I demonstrate how to use Terraform’s new aws_dynamodb_global_secondary_index resource to manage GSI drift selectively. I walk you through the limitations of current approaches and guide you through implementing the solution.

The ability to invoke Lambda functions in response to Amazon RDS for SQL Server database events enables powerful use cases such as triggering automated workflows, sending real-time notifications, calling external APIs, and orchestrating complex business processes. In this post, we demonstrate how to enable this integration by using Amazon CloudWatch subscription filters, Amazon SQS, and Amazon SNS to invoke Lambda functions from RDS for SQL Server stored procedures, helping you build responsive, data-driven applications.

In this post, we show how you can use graph algorithms to analyze the results of AWS Entity Resolution and related transactions for the CNP use case. We use several AWS services, including Neptune Analytics, AWS Entity Resolution, Amazon SageMaker notebooks, and Amazon S3.

In this post, we give insights into Aurora DSQL Auto Analyze, a probabilistic and de-facto stateless method to automatically compute DSQL optimizer statistics. Users who are familiar with PostgreSQL will appreciate the similarity to autovacuum analyze.

In this post, we show you how to validate Neo4j Cypher queries before migrating to Neptune using the openCypher Compatibility Checker tool. You can use this tool to identify compatibility issues early in your migration process, reducing migration time and effort.

In this post, we walk you through two methods to automate your Neo4j database to Neptune using the neo4j-to-neptune utility. This tool offers a fully automated end-to-end process in addition to a step-by-step manual process.

Today, we’re announcing multi-account global tables for Amazon DynamoDB, which let you replicate DynamoDB table data across multiple AWS accounts and AWS Regions. This feature adds account-level isolation to global tables, so you can replicate DynamoDB table data across multiple AWS accounts and Regions for stronger isolation and resiliency. In this post, we show you how to create and configure a multi-account global table, and introduce use cases highlighting the value of using this feature.

In this post, we talk about the benefits of caching in generative AI applications. We also elaborated on a few implementation strategies that can help you create and maintain an effective cache for your application.

Amazon Keyspaces now supports the pre-warming feature to provide you with proactive throughput management. With pre-warming, you can set minimum warm throughput values that your table can handle instantly, avoiding the cold start delays that occur during dynamic partition splits. In this post, we discuss the Amazon Keyspaces pre-warming feature capabilities and demonstrate how it can enhance your throughput performance.