AWS Database Blog

Category: Intermediate (200)

Build and deploy knowledge graphs faster with RDF and openCypher

Amazon Neptune Analytics now supports openCypher queries over RDF graphs. When you build an application that uses a graph database such as Amazon Neptune, you’re typically faced with a technology choice at the start: There are two different types of graphs, Resource Description Framework (RDF) graphs and labeled property graphs (LPGs), and your choice of […]

Monitor Amazon DynamoDB operation counts with Amazon CloudWatch

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.

Better Together: Amazon SageMaker Canvas and RDS for SQL Server, a predictive ML model sample use case

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.

Review your Amazon Aurora and Amazon RDS security configuration with Prowler’s new checks

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.

Query RDF graphs using SPARQL and property graphs using Gremlin with the Amazon Athena Neptune connector

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.

Introducing smaller capacity units for Amazon Neptune Analytics: Up to 75% cheaper to get started with graph analytics workloads

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.

Best practices for Amazon RDS for SQL Server with Amazon EBS io2 Block Express volumes up to 64 TiB

Amazon RDS for SQL Server now supports Amazon EBS io2 Block Express volumes. These volumes are designed to support all your critical database workloads that demand high performance, high throughput, and consistently low latency. io2 Block Express volumes support 99.999% durability, up to 64 TiB storage, up to 4,000 MiB/s throughput, and up to 256,000 Provisioned IOPS for your most demanding database needs, at the same price as EBS io1 volumes. In this post, we share best practices to use the io2 Block Express volumes with RDS for SQL Server DB instances.

Schneider Electric automates Salesforce account hierarchy management with generative artificial intelligence (AI) using Amazon Aurora and Amazon Bedrock

Schneider Electric is a leader in digital transformation in energy management and industrial automation. To effectively manage customer account hierarchies in its CRM at scale, Schneider Electric started leveraging advances in generative artificial intelligence (AI) large language models (LLMs) in April 2023. They created a solution to make timely updates to their customer account hierarchies in their CRM by linking customer account information to the correct parent company based on the latest information retrieved from the Internet and proprietary datasets. In this post, we explore further iterations of this project and how the team applied what they learned to the Salesforce CRM system using Amazon Aurora and Amazon Bedrock.

Implement UUIDv7 in Amazon RDS for PostgreSQL using Trusted Language Extensions

UUID Version 7 (UUIDv7) was introduced to improve the randomness of UUIDv4. UUIDv7 encodes a Unix timestamp with millisecond precision in the first 48 bits of the UUID, meaning that UUIDv7 is time-based and sequential. Trusted Language Extensions (pg_tle) for PostgreSQL is a new open source development kit to help you build high performance extensions that run safely on PostgreSQL. In this post, we demonstrate how to create and install a Trusted Language Extension (TLE) using PL/Rust as the trusted language to generate a UUIDv7. We also take a deeper look into the underlying implementation of the extension.

Run an Ethereum staking service on Amazon EKS

In September 2022, Ethereum transitioned to a Proof of Stake (PoS) consensus model. This change allows anyone with a minimum of 32 ether to stake their holdings and operate a validator node, thereby participating in network validation and earning staking rewards. In this post, we explore the technical challenges and requirements of operating an institutional-grade Ethereum staking service. Additionally, we outline a solution for deploying an Ethereum staking service on AWS.