AWS Database Blog

Category: Amazon Neptune

Load RDF data into Amazon Neptune with AWS Glue

In this post, we present a design for a common technical requirement: ingest data from multiple sources to a target Resource Description Framework (RDF) graph database. Our target is Amazon Neptune, a managed graph database service. RDF is one of two graph models supported by Neptune. The other is Labeled Property Graph (LPG). Each graph […]

Empowering fraud detection at Delivery Hero with Amazon Neptune

This is a guest post co-authored by Amr Elnaggar, Saurabh Deshpande, Mohammad Azzam, Matias Pons and Wilson Tang from Delivery Hero. Delivery Hero is available in 74 countries around the World. It operates a wide range of local brands that are united behind the shared mission Always Delivering an Amazing Experience — fast, easy, and […]

How NXP performs event-driven RDF imports to Amazon Neptune using AWS Lambda and SPARQL UPDATE LOAD

For manufacturers it’s important to track transformations and transfers of products as they travel through the supply chain. In the event of quality issues, the ability to quickly and accurately identify a defective product and gather data for root cause analysis and containment is critical. NXP Semiconductors has been working to improve its product traceability […]

Automated testing of Amazon Neptune data access with Apache TinkerPop Gremlin

Amazon Neptune, a fully managed graph database, is purpose built to work with highly connected data such as relationships between customers and products, or between pieces of equipment within a complex industrial plant. Neptune is designed to support highly concurrent online transaction processing (OLTP) over graph data models. Neptune supports both property graphs, which you […]

How Informatica® Cloud Data Governance and Catalog uses Amazon Neptune for knowledge graphs

This post was co-written with Tiju Titus John and Deepak Ram from Informatica. In this post, we discuss the significance of data governance and cataloging, and how Informatica®’s latest product can help enterprises address challenges in this area of high complexity. We also discuss how Informatica® uses a graph database solution based on Amazon Neptune […]

Uncover financial fraud with Amazon Neptune and Tom Sawyer Perspectives

This is a guest post written by Janet M. Six, Senior Product Manager at Tom Sawyer Software. Fraud and corruption affect the lives of millions of people by impacting the financial health of corporations and individuals. Fraud is typically carried out by multiple parties that, by their very nature, strive to remain hidden in plain […]

Automate the stopping and starting of Amazon Neptune environment resources using resource tags

Automating the management of the compute resources associated with your Amazon Neptune database cluster can save you time and money. The most significant cost when running Neptune for your graph workloads are the compute resources in the database cluster. If you’re also using associated resources such as Amazon SageMaker notebook instances, which you can use […]

Fine Grained Access Control for Amazon Neptune data plane actions

Amazon Neptune is purpose-built to store and navigate relationships. This provides advantages over relational databases for use cases like social networking, recommendation engines, and fraud detection, where you need to create relationships between data and quickly query these relationships. At AWS, security is Job Zero. Neptune offers several security features, including network isolation, encryption, and […]

Introducing Amazon Neptune Global Database

Today, Amazon Neptune announced the general availability of Amazon Neptune Global Database. You can use Neptune Global Database to build graph applications across multiple AWS Regions using the same graph database. Neptune Global Database is available in the US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Europe (Ireland), Europe […]

Discover new insights from your data using SQL Server Integration Services (SSIS) and Amazon Neptune

A relational database is like a multitool: it can do many things, but it’s not perfectly suited to all tasks. For example, suppose a police department has been using a relational database to perform crime data analysis. As their breadth of sources and volume of data grows, they start to experience performance issues in querying […]