AWS Database Blog

Amazon DynamoDB continuously sends metrics about its behavior to Amazon CloudWatch. Something I’ve heard customers ask for is how to get a count of successful requests of each operation type (for example, how many GetItem or DeleteItem calls were made) in order to better understand usage and costs. In this post, I show you how to retrieve this metric.

In this post, we demonstrate how to swiftly deploy Stacks blockchain nodes on AWS with the AWS Blockchain Node Runners blueprint.

When workloads and their corresponding transactional databases are distributed across multiple cloud providers, it can create challenges in using the data in near real time for advanced analytics. In this post, we discuss architecture, approaches, and considerations for streaming data changes from the transactional databases deployed in other cloud providers to a streaming data solution deployed on AWS.

Data within public blockchain networks such as Bitcoin and Ethereum can be accessed by anyone. However, accessing and making sense of this information has traditionally been a complex and technical undertaking. Much of the data is encoded and stored as bytes, rather than in a human-readable format. In this post, we introduce a solution that demonstrates how you can chat with blockchain data using Amazon Bedrock and the AWS Public Blockchain datasets. We discuss Amazon Bedrock, review the solution architecture, provide example prompts, share interesting findings, and go over how you can extend the solution to integrate with different data sources.

As businesses strive to integrate AI/ML capabilities into their customer-facing services and solutions, they often face the challenge of leveraging massive amounts of relational data hosted on on-premises SQL Server databases. This post showcases how Amazon Relational Database Service (Amazon RDS) for SQL Server and Amazon SageMaker Canvas can work together to address this challenge. By leveraging the native integration points between these managed services, you can develop integrated solutions that use existing relational database workloads to source predictive AI/ML models with minimal effort and no coding required.

In today’s rapidly advancing world of generative artificial intelligence (AI), businesses across diverse industries are transforming customer experiences through the power of real-time search. By harnessing the untapped potential of unstructured data ranging from text to images and videos, organizations are able to redefine the standards of engagement and personalization. A key component of this […]

In this post, we discuss the steps to perform a blue/green deployment switchover and how to set up and perform a rollback strategy post switchover for Amazon Aurora MySQL-Compatible Edition.

Prowler for AWS provides hundreds of security configuration checks across services such as Amazon Redshift, Amazon ElasticCache, Amazon API Gateway, Amazon CloudFront, and many more. In this post, we focus on these new and expanded Amazon RDS security checks, their integration with AWS Security Hub, and the benefits they offer AWS users.

Homogeneous data migrations in AWS DMS simplify the migration of on-premises databases to their Amazon RDS equivalents. In this post, we guide you through the steps of performing a homogeneous migration from an on-premises MySQL database to Amazon Aurora MySQL using AWS DMS homogeneous data migrations over a private network using network load balancer.

To query a Neptune database in Athena, you can use the Amazon Athena Neptune connector, an AWS Lambda function that connects to the Neptune cluster and queries the graph on behalf of Athena. In this post, we provide a step-by-step implementation guide to integrate the new version of the Athena Neptune connector and query a Neptune cluster using Gremlin and SPARQL queries.