Overview of Amazon Neptune features

This section provides an overview of specific Neptune features, including:

• Neptune compliance with query-language standards.

• Neptune's graph data model.

• An explanation of Neptune transaction semantics.

• An introduction to Neptune clusters and instances.

• Neptune's storage, reliability and availability.

• An explanation of Neptune endpoints.

• How Neptune's custom query IDs let you check query status.

• Using Neptune's lab mode to enable experimental features.

• A description of Neptune's DFE engine.

• Neptune's JDBC connectivity.

• A list of Neptune engine releases and how to update your engine.

Note

This section does not cover using the query languaged that you can use to access the data in a Neptune graph.

For information about how to connect to a running Neptune DB cluster with Gremlin, see Accessing a Neptune graph with Gremlin.

For information about how to connect to a running Neptune DB cluster with openCypher, see Accessing the Neptune Graph with openCypher.

For information about how to connect to a running Neptune DB cluster with SPARQL, see Accessing the Neptune graph with SPARQL.

Topics

• Notes on Amazon Neptune Standards Compliance
• Neptune Graph Data Model
• The Neptune lookup cache can accelerate read queries
• Transaction Semantics in Neptune
• Amazon Neptune DB Clusters and Instances
• Amazon Neptune storage, reliability and availability
• Connecting to Amazon Neptune Endpoints
• Inject a Custom ID Into a Neptune Gremlin or SPARQL Query
• Neptune Lab Mode
• The Amazon Neptune alternative query engine (DFE)
• Managing statistics for the Neptune DFE to use
• Getting a quick summary report about your graph
• Amazon Neptune JDBC connectivity
• Amazon Neptune engine updates