AWS re:Invent 2022 - Deep dive into Amazon Neptune Serverless (DAT322)

With the launch of Amazon Neptune Serverless, graph database workloads can automatically scale from one query to hundreds of thousands of queries. In this deep-dive session, discover how serverless addresses not only workloads with sudden spikes but also those that are unpredictable while providing customers up to 90 percent cost savings compared to provisioning for peak capacity.


Subscribe:

ABOUT AWS
Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.

AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

#reInvent2022 #AWSreInvent2022 #AWSEvents

[andreyb]

Could someone, please, post a link to a working solution when Neptune is queried through API gateway and lambda using SPARQL.
Ideally not a Graphql api but just a simple api with free form text sparql query.
Assume that Jupyter notebook is not a case and all graph rendering/editing happen in WEB UI. OpenCypher is also interesting if schema less.