Access & Analyze Data
This section includes information about the ways you can access the data that is stored in Graph Lakehouse.
Gives a tour of the Graph Lakehouse user interface and includes instructions on logging in.
Information on accessing and using the Graph Lakehouse command line interface, azgi.
Use Third-Party Visualization Tools
Information on accessing data from graph visualization tools such as Apache Zeppelin and Jupyter Notebook.
Access the SPARQL and RDF Endpoints
Information on accessing the standard W3C SPARQL Protocol and SPARQL Graph Store HTTP Protocol endpoints for sending and receiving SPARQL requests.
Access Data with OData Protocol
Information on creating and accessing Data on Demand endpoints for Open Data Protocol (OData)-based feeds that can be used with business intelligence tools.
Instructions on creating virtual or materialized views to hide the complexity of the data, combine data from one or more graphs or views, or mask sensitive information.
Information on creating query definitions that you can reuse as subqueries in other queries.
SPARQL Query Language Reference
Reference information on Graph Lakehouse's built-in functions and SPARQL extension libraries.
Cypher Query Language Reference
Information on Graph Lakehouse's Cypher language support and compatibility with Cypher as documented by the openCypher community group.