A lot of applications being built today need to understand and navigate relationships between highly connected data to enable use cases like social applications, recommendation engines, fraud detection, knowledge graphs, life sciences, and IT/network. Because the data is highly connected, it is easily represented as a graph, which is a data structure that consists of vertices and directed links called edges. Vertices and edges can each have properties associated with them. The diagram below depicts a simple graph of relationships between friends and their interests. A graph database is optimized to store and process graph data. 

What is a Graph Database?

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Amazon Web Services (AWS) provides a variety of graph database options. Amazon Neptune provides a fast, reliable, fully managed graph database service. You can also operate your own graph database in the cloud on Amazon EC2 and Amazon EBS and work with AWS solution providers.

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Deep dive on Amazon Neptune

Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. It is optimized for storing billions of relationships and querying the graph with milliseconds latency. Neptune supports the popular graph query languages Apache TinkerPop Gremlin and W3C’s SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. 

Amazon Neptune is highly available, with read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across Availability Zones. Neptune is secure, with support for encryption at rest and in transit. Neptune is fully-managed, so you no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups.

JanusGraph is the modern fork of the popular Titan Graph database. It is designed to efficiently store and traverse both small and large graphs up to hundreds of billions of vertices and edges. JanusGraph enables scalability through a pluggable storage engine architecture.

The Amazon DynamoDB Storage Backend for JanusGraph enables you to store JanusGraph graphs of any size in fully-managed DynamoDB tables. With the DynamoDB storage backend plugin for JanusGraph, you can offload JanusGraph storage management to AWS. JanusGraph’s pluggable architecture makes it easy to start using DynamoDB without changing your application.

The Amazon DynamoDB Storage Backend for Titan enables you to store Titan graphs of any size in fully-managed DynamoDB tables. With the DynamoDB storage backend plugin for Titan, you can offload Titan storage management to AWS. Titan’s pluggable architecture makes it easy to start using DynamoDB without changing your application.

JanusGraph supports the latest Tinkerpop version, a collection of graph processing and analysis tools. For more information, see the Working with Graph Databases section of our Documentation »

Neo4j offers a shared-nothing architecture with a single write master and multiple read replicas. Neo4j supports its own Cypher query language as well as Gremlin. To give it a try, launch a Neo4j test drive from our big data page »

OrientDB supports schema-less, schema-full, and schema-mixed modes. It includes support for SQL and extends the language to support concepts such as trees and graphs. To get started using OrientDB, visit the AWS Marketplace »

GraphDB is a resource description framework (RDF) graph database that supports text mining, SPARQL queries, semantic annotation, and semantic search. To get started using GraphDB, visit the AWS Marketplace »