A graph database stores vertices and directed links called edges. Graphs can be built on relational (SQL) and non-relational (NoSQL) databases. Vertices and edges can each have properties associated with them. The diagram below depicts a simple graph of relationships between friends and their interests. To learn more about graph databases, read the AWS Activate blog post »
To learn more about building a graph database on AWS using Amazon DynamoDB and Titan, read this post on the AWS Big Data Blog »
Titan is a popular graph database designed to efficiently store and traverse both small and large graphs up to hundreds of billions of vertices and edges. Titan enables scalability through a pluggable storage engine architecture.
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.
Titan supports Tinkerpop, a collection of graph processing and analysis tools, including Gremlin and Blueprints. For more information, see the Working with Graph Databases section of our Documentation »
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 »