Abstract: A system is disclosed to build and store a conceptual model and queries for a graph database. In various embodiments, data defining one or more aspects of a conceptual model associated with a graph database is received. A logical model of the conceptual model is created based at least in part on the conceptual model. The logical model includes information defining how data is physically stored. A set of data that represents the conceptual model is stored as a graph that includes one or more nodes to represent each of the following: conceptual model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: A graph-based data privacy compliance solution is disclosed. In various embodiments, a privacy graph database based at least in part on an associated privacy graph model is stored. The privacy graph database is used to manage private information of a person, including by including in the privacy graph database: a node instance associated with the person and a corresponding node representing an element of the private information of the person, wherein the corresponding node is connected to the node instance associated with the person. A data lineage for the element of the private information of the person is determined including by identifying the corresponding node representing the element of the private information of the person; and traversing the privacy graph database to identify one or more nodes related by a sequential relationship, each of the one or more nodes being associated with a corresponding event that occurred with respect to the element of the private information of the person.

Abstract: A graph-based data privacy compliance solution is disclosed. In various embodiments, a privacy graph database based at least in part on an associated privacy graph model is used to store private information of a person, including by including in the privacy graph database a node representing a critical data element comprising the private information of the person.

Abstract: Techniques are disclosed to provide a graph based recommendation system. A recommendation engine definition that includes for each of a plurality of pipeline phases a corresponding phase definition and data indicating a location of the phase in a pipeline defined by the recommendation engine definition is stored in a memory of other storage device. The recommendation engine definition is used to generate programmatically one or more procedures to provide a recommendation engine that implements the pipeline. An API usable by a client to obtain a recommendation from the recommendation engine is generated programmatically and exposed.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

Abstract: Techniques are disclosed to provide a graph based recommendation system. A recommendation engine definition that includes for each of a plurality of pipeline phases a corresponding phase definition and data indicating a location of the phase in a pipeline defined by the recommendation engine definition is stored in a memory of other storage device. The recommendation engine definition is used to generate programmatically one or more procedures to provide a recommendation engine that implements the pipeline. An API usable by a client to obtain a recommendation from the recommendation engine is generated programmatically and exposed.

Abstract: Techniques are disclosed to provide a graph based recommendation system. A recommendation engine definition that includes for each of a plurality of pipeline phases a corresponding phase definition and data indicating a location of the phase in a pipeline defined by the recommendation engine definition is stored in a memory of other storage device. The recommendation engine definition is used to generate programmatically one or more procedures to provide a recommendation engine that implements the pipeline. An API usable by a client to obtain a recommendation from the recommendation engine is generated programmatically and exposed.

Abstract: A system is disclosed to build and store a data model and queries for a graph database. In various embodiments, data defining one or more aspects of a data model associated with a graph database is received. A set of data that represents the data model is stored as a graph that includes one or more nodes to represent each of the following: data model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.