Amazon Neptune Global Database
Overview
Amazon Neptune Global Database is designed for globally distributed applications, allowing a single Neptune database to span multiple AWS Regions. It replicates your data with little impact to database performance, enables fast local reads with low latency in each Region, and provides disaster recovery in case of region-wide outages. With Neptune Global Database, you can now deploy a primary Neptune database cluster in one AWS Region and replicate its data in up to five secondary read-only database clusters (with up to 16 read replicas each) in different AWS Regions.
Neptune Global Database uses storage-based replication with typical latency of less than 1 second, using dedicated infrastructure that leaves your database fully available to serve application workloads. In the unlikely event of an AWS Regional degradation or outage, one of the secondary AWS Regions can be promoted to read and write capabilities in a Neptune Global Database.
Neptune Global Database benefits
Subsecond data access in any Region
Cross-Region disaster recovery
Pricing
With Neptune Global Database, you pay for the resources used in the AWS Regions where your Neptune cluster is present based on the on-demand Neptune instance and for storage prices for that Region. In addition, you pay for replicated write I/Os, which will capture writes, inserts, and deletes between the primary and each secondary cluster. For full pricing and Regional availability see Neptune pricing.
Getting started
Get started with Neptune, a fully managed graph database
Neptune is a fast, reliable, fully managed graph database service that makes it easier to build and run applications that work with highly connected datasets. The core of Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Neptune supports popular graph models property graph and W3C's RDF and their respective query languages openCypher, Apache TinkerPop Gremlin, and SPARQL, allowing you to more easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and IT security.