Best Practice
Graph Lakehouse is a high performance graph OLAP database that lets users perform BI-style analytics with unparalled speed and scalability. Graph Lakehouse supports parallel loading of data so users can begin performing analytics on data quickly. Graph Lakehouse uses standards from the W3C regarding RDF data formats and the SPARQL query language.
Graph Lakehouse can be deployed in cloud environments such as Amazon AWS, Google Cloud, Microsoft Azure, and IBM Cloud Pak, or on-premises on Linux bare metal and virtual machines. Graph Lakehouse also supports Docker and Kubernetes deployments with data staged locally or in shared NFS, HDFS, or object storage. This section provides an overview of Graph Lakehouse features and architecture.
Details about the key Graph Lakehouse features and the benefits that they provide.
An overview of Graph Lakehouse's data storage and query processing architecture.
Planning & Deployment Guidelines
Guidance on choosing an appropriate system design and configuration for Graph Lakehouse.
Securing a Graph Lakehouse Environment
Recommendations to follow to strengthen the security of Graph Lakehouse environments.