Amazon Neptune DB was announced by Amazon Web Services (AWS) in November 2017 and became generally available in May 2018. It was developed to address the need for a fully managed graph database service that could handle complex, highly connected datasets efficiently. AWS created Neptune to support both property graph and RDF graph models, enabling users to leverage graph databases for applications like recommendation engines and fraud detection with ease and scalability.
Amazon Neptune DB
Amazon Neptune DB is a fully managed graph database service designed to work with highly connected datasets. It supports popular graph models like property graphs and RDF, enabling efficient storage and querying of complex relationships using languages such as Gremlin and SPARQL. Neptune is optimized for handling billions of relationships and querying the graph with low latency, making it suitable for use cases like recommendation engines, fraud detection, knowledge graphs, and network security.
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About Amazon Neptune DB
Strengths of Amazon Neptune DB include its fully managed nature, support for both property graph and RDF models, scalability, and low-latency querying capabilities. Weaknesses may involve potential vendor lock-in and limitations in customization compared to self-managed solutions. Competitors include Microsoft Azure Cosmos DB, Neo4j, and Google Cloud's Firestore with graph capabilities.
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How to hire a Amazon Neptune DB expert
An Amazon Neptune DB expert should have skills in graph database modeling and design, proficiency in query languages like Gremlin and SPARQL, and experience with AWS services for integration and management. They should also understand data migration strategies to Neptune, performance optimization techniques for graph queries, and security best practices within AWS environments.
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