AWS Database Blog

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune’s database engine is optimized for storing billions of relationships and querying with millisecond latency. The W3C’s Resource Description Framework (RDF) model and the popular Labeled Property Graph model […]

Amazon Neptune ML provides a simple workflow for training machine learning (ML) models for graph data. With version 1.0.5.0, Neptune ML delivers additional enhancements to all the steps of this workflow to reduce cost, increase speed, and offer a more flexible modeling experience. Starting with data export and data processing, Neptune ML now provides additional […]

As an application developer building graph applications with Amazon Neptune, your graph data may be evolving on a regular basis, with new nodes and or new relationships between nodes being added to the graph to reflect the latest changes in your underlying business data. Amazon Neptune ML now supports incremental model predictions on graph data […]

Amazon Neptune ML is a feature of Amazon Neptune that brings the power of the state-of-the-art graph neural network (GNN) models to all graph developers. You can use Neptune ML for tasks like node classification, node regression, and link prediction. This allows you to train GNN models powered by the Deep Graph Library (DGL) to […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. With the announcement of Amazon CloudWatch Metric Streams, you can now stream near-real-time metrics data to a destination such as Amazon Simple Storage Service (Amazon S3). Metric Streams supports two primary use […]

In this series of posts (Part 1, Part 2, Part 3 and Part 4) , we compare and contrast the disaster recovery (DR) solutions available for SQL Server on Amazon Elastic Compute Cloud (Amazon EC2) and help you understand the nature of these trade-offs, and the cost and complexity of implementing DR for SQL Server […]

In this series of posts (Part 1, Part 2, Part 3 and Part 4), we compare and contrast the disaster recovery (DR) solutions available for Microsoft SQL Server on Amazon Elastic Compute Cloud (Amazon EC2) and help you understand the nature of these trade-offs, and the cost and complexity of implementing DR for SQL Server […]

In this series of posts (Part 1, Part 2, Part 3 and Part 4), we compare and contrast the disaster recovery (DR) solutions available for Microsoft SQL Server on Amazon Elastic Compute Cloud (Amazon EC2). This post introduces three methods for implementing DR for SQL Server on AWS: SQL Server backup and restore, SQL Server […]

In today’s world, it’s just a matter of time before disaster happens, and when it happens it’s essential to recover your SQL Server databases and bring the systems online with minimal data loss and downtime. To respond to and recover from an outage of SQL Server database access, high availability (HA) and disaster recovery (DR) […]

Today, we announced that openCypher for Amazon Neptune is available in lab mode. Developers can now use openCypher and Apache TinkerPop Gremlin to build or migrate property graph applications. Neptune’s purpose-built graph engine now supports three open graph query languages: Apache TinkerPop Gremlin, openCypher, and the World Wide Web Consortium’s (W3C) SPARQL 1.1, giving developers […]