AWS Database Blog

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 HAQM Relational Database Service (HAQM RDS) for SQL Server and HAQM 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 HAQM Aurora MySQL-Compatible Edition.

Prowler for AWS provides hundreds of security configuration checks across services such as HAQM Redshift, HAQM ElasticCache, HAQM API Gateway, HAQM CloudFront, and many more. In this post, we focus on these new and expanded HAQM 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 HAQM RDS equivalents. In this post, we guide you through the steps of performing a homogeneous migration from an on-premises MySQL database to HAQM 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 HAQM 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.

Stopping and starting the RDS Multi-AZ DB clusters can be very useful if you want to temporarily stop the clusters for your development or test environments when you’re not using them for various reasons (such as vacations, holidays, or weekends) to reduce costs. In this post, we show you how to stop and start your RDS Multi-AZ DB clusters, enabling you to gain more control over your infrastructure resources.

Retrieval Augmented Generation (RAG) is an innovative approach that combines the power of large language models with external knowledge sources, enabling more accurate and informative generation of content. Using knowledge graphs as sources for RAG (GraphRAG) yields numerous advantages. These knowledge bases encapsulate a vast wealth of curated and interconnected information, enabling the generation of responses that are grounded in factual knowledge. In this post, we show you how to build GraphRAG applications using HAQM Bedrock and HAQM Neptune with LlamaIndex framework.

In this post, we talk about how Infosys redefined the ETL landscape for their product sales and freight management application using Aurora zero-ETL to HAQM Redshift. We also explain our experience with the old process and how the new zero-ETL integration helped us effortlessly move data into a Redshift cluster for analytics along with metrics to monitor the health of the integration.

In this post, we show how you can reduce your cost by up to 75% when getting started with graph analytics workloads using the new 32 and 64 m-NCU capacities for Neptune Analytics. Many commonly used sample datasets can fit on 32 or 64 m-NCU, allowing you to work with the same data but at a lower cost. We also discuss how to monitor the graph size and resize m-NCUs without downtime.