Amazon Neptune is a fully managed graph database service. After launching an Amazon Neptune instance, you can connect to it using any client that supports Apache TinkerPop Websocket Server or the W3C’s SPARQL Protocol 1.1.

We have published AWS Reference Architectures for Using Graph Databases to help inform your choices about graph data models and query languages as well as providing reference deployment architectures. Below you will find the resources you need to get started with Amazon Neptune.  

Recent blog posts

No blog posts have been found at this time. Please see the AWS Blog for other resources.

See all Amazon Neptune posts on the AWS Database Blog

 

AWS Tech Talks

Build Event Driven Graph Applications with AWS Purpose-Built Databases (48:03)
Understanding Game Changes and Player Behavior with Graph Databases (50:21)

AWS re:Invent 2019

AWS re:Invent 2019: Deep dive on Amazon Neptune (1:01:01)
AWS re:Invent 2019: Real-world customer use cases with Amazon Neptune (30:25)

AWS re:Invent 2018

AWS re:Invent 2018: Building a Social Graph at Nike with Amazon Neptune (53:46)
AWS re:Invent 2018: Data & Analysis with Amazon Neptune: A Study in Healthcare Billing (48:49)
AWS re:Invent 2018: Deep Dive on Amazon Neptune (1:00:42)
AWS re:Invent 2018: How Do I Know I Need an Amazon Neptune Graph Database? (46:12)

AWS Tel Aviv Summit 2018

AWS Tel Aviv Summit 2018: How Amazon Neptune and Graph Databases Can Transform Your Business (38:39)

Twitch Neptune Launch Interview

Amazon Neptune: Build Applications for Highly Connected Datasets (32:33)

AWS re:Invent 2017

AWS re:Invent 2017: Deep Dive on Amazon Neptune (58:19)
AWS re:Invent 2017 Launchpad - Amazon Neptune (16:12)
AWS re:Invent 2017: Amazon Neptune Overview and Customer Use Cases (1:00:56)
AWS re:Invent 2017: Graph-based Approaches for Cyber Investigative Analytics (47:41)

Customer case studies

Capital One
“A graph database gives us more flexibility than the relational systems. We might need to do a lot of joins on our tables [in a relational model], and that would have caused high latency of a lot of our business logic. A graph database is optimized for our use case. Amazon Neptune solved what we were trying to solve.”

Mayank Gupta, Software Engineer - Audible for Business

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Capital One

metaphactory and Amazon Neptune enabled Siemens Energy to build a Turbine Knowledge Graph and visualize the connections between similar parts across the entire fleet of gas turbines. Amazon Neptune, a managed graph database service, fits perfectly into the cloud-first strategy driven by Siemens Energy IT, which focuses on reliability, scalability, reduction of maintenance and integration with their existing platform on Amazon Web Services (AWS).

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Enkidoo
"We chose Neptune because it is a powerful graph database that is secure, performant, and analytics-friendly. In our [contact tracing] model, each user node is connected to a device node. When a device checks in to a location, an edge forms between that device and a scannable (a QR code), which is associated with a particular site (a physical store) and linked organization (a corporate entity). Neptune allows us to store these rich relationships between users, check-ins, and locations to derive insight about the spread of the virus."

Aron Szanto, Co-Founder - Zerobase

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Zeta
“By leveraging [Amazon] Neptune and other AWS services, we are able to achieve a cost-efficient data platform, at scale, in a very short period of time.”

Sasikala Singamaneni, Software Engineering Manager - Zeta Global

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