The Amazon Neptune Service provides high-performance graph analytics and serverless database for superior scalability and availability. Amazon Neptune Database is a serverless graph database designed for superior scalability and availability. Neptune Database provides built-in security, continuous backups, and integrations with other AWS services. Amazon Neptune Analytics is an analytics database engine for quickly analyzing large volumes of graph data to get insights and find trends from data stored in Amazon S3 buckets or a Neptune database. Neptune Analytics uses built-in algorithms, vector search, and in-memory computing to run queries on data with tens of billions of relationships in seconds.
This white paper aims to guide customers on how they improve the quality of GenAI applications using graphs to significantly enhance the capabilities of GenAI applications, ultimately driving competitive advantages and innovation.
A software bill of materials (SBOM) is one of the pillars of risk management and cybersecurity. As the scope and complexity of cyberthreats increase, the development and adoption of secure SBOMs, combined with graphs, emerge as a critical imperative to safeguard an organization’s digital infrastructure.
In this blog, we demonstrate how to discover and visualize the actual graph schema directly from the data that resides within an Amazon Neptune database.
Because of Amazon Neptune, Audible for Business has hit the ground running and tapped into an up-and-coming market: helping businesses support their team members in new and significant ways.
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More people than ever are aware of world events highlighting the lack of diversity, equity and inclusion due to social media, news coverage and increased community dialogue on the topics. As a result, people are much more aware of the importance of DEI initiatives in all areas of life—whether in their personal lives or at work.
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Amazon Neptune ML is a new capability of Neptune that uses graph neural networks (GNNs), a machine learning (ML) technique purpose-built for graphs, to make easy, fast, and more accurate predictions using graph data.
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In this post, we demonstrated how to successfully migrate a database when the total size of the database and backup exceeds 16 TB by using FSX for Windows File Server. This method also lets you avoid overprovisioning storage for RDS Custom for SQL Server while transferring very large databases, thereby reducing costs.
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To create a better experience for its players, MovieStarPlanet decided to modernize its architecture. By modernizing using microservices on Amazon Web Services (AWS), MovieStarPlanet improved engagement and retention, reduced dynamic hosting costs by over 40 percent, and increased developer productivity, helping create new experiences for players.
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