AWS Database Blog
Category: Technical How-to
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.
Stop and start Amazon RDS Multi-AZ DB clusters on a schedule
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.
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune
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 Amazon Bedrock and Amazon Neptune with LlamaIndex framework.
Implementing a fall forward strategy from Amazon RDS for SQL Server Transparent Data Encryption (TDE) and Non-TDE Enabled databases to self-managed SQL Server
In this post, we discuss how to set up a rollback strategy using a fall forward approach from Amazon RDS for SQL Server transparent database encryption (TDE)- and non-TDE-enabled databases to self-managed SQL Server, utilizing SQL’s native backup and restore option.
Make relevant movie recommendations using Amazon Neptune, Amazon Neptune Machine Learning, and Amazon OpenSearch Service
In this post, we discuss a design for a highly searchable movie content graph database built on Amazon Neptune, a managed graph database service. We demonstrate how to build a list of relevant movies matching a user’s search criteria through the powerful combination of lexical, semantic, and graphical similarity methods using Neptune, Amazon OpenSearch Service, and Neptune Machine Learning. To match, we compare movies with similar text as well as similar vector embeddings. We use both sentence and graph neural network (GNN) models to build these embeddings.
Use the AWS InfluxDB migration script to migrate your InfluxDB OSS 2.x data to Amazon Timestream for InfluxDB
AWS has partnered with InfluxData to launch Amazon Timestream for InfluxDB, a managed version of the popular InfluxDB 2.x open source time series database engine. In this post, we demonstrate how to use the AWS InfluxDB migration script to migrate your data from your existing InfluxDB OSS 2.x instances to Timestream for InfluxDB. At the end of this post, we show one way to perform a live migration, with additional AWS resources.
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.
Export Amazon RDS for MySQL and MariaDB databases to Amazon S3 using a custom API
As customers are migrating to the AWS Cloud to take advantage of managed database services such as Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora MySQL-Compatible Edition, they also look to automate these administrative tasks. This post shows how a DBA or other user with access to a custom API can make MySQL and MariaDB backup requests. It uses Infrastructure as Code (IaC) with the AWS CDK to simplify the deployment.
Achieve near real-time analytics with Amazon DynamoDB and zero-ETL for Amazon OpenSearch Service
In this post, we explore how to transition from using Rockset to OpenSearch Service for your DynamoDB use-case effectively. To illustrate this integration, we consider a real-world example of a gaming company that tracks user interactions, such as in-game purchases and player scores, using DynamoDB. This data needs to be analyzed in real time to provide insights into user behavior, detect anomalies, and personalize the gaming experience.
Use Oracle Real Application Clusters as a source for AWS DMS
In this post, we explore the steps to configure Oracle RAC as a source for AWS DMS.