Abstract: Detection and use of relationships in tabular data is enhanced. A foreign-key-based relationship between two tables in memory is automatically discovered by a module. A view over table data is computationally augmented by adding an expandable hierarchical column. The expandable hierarchical column includes second table data that is related to rows of a first table by the discovered foreign-key-based relationship. A naming scheme for the added column is described. Sometimes the augmentation places an AddJoinColumn operator in a query expression tree; sometimes the tree is rewritten by moving a query operator or replacing a specified pattern of operators by a flat Join operation between two tables. Column expansion may be followed by reshaping data into a flat table, by getting a homogeneous query, by performing a join, or other operations.

Abstract: In an embodiment, a generic database application of a computer system receives a portion of input data from a database. The generic database application can communicate with the database using a variety of different database schemas. The generic database application of the computer system infers a portion of ORM metadata associated with the received input data. The computer system accesses a generic ORM query where the ORM query is configured to provide mapping information to map the input data into a graph of objects according to the database object properties included in the ORM metadata. The computer system maps the input data into a graph of objects using the database object properties included in the ORM metadata and displays an ORM object view which includes the graph of objects.

Abstract: In an embodiment, a computer system defines a generic relational meta-schema (GRMS), where the GRMS describes a generic representation for relational schemas and where the GRMS includes metadata indicating how a relational schema is to be stored as data in the data store. The computer system also defines describes a generic relational data schema (GRDS), where the GRDS describes a generic representation for relational data and where the GRDS includes metadata that indicates how relational data is to be stored in the data store in a generic fashion not necessarily complying with the relational schema for the data. Next, the computer system stores data in the data store according to the generic relational data schema and stores metadata as data in the data store according to the generic relational meta-schema.

Abstract: In an embodiment, a generic database application of a computer system receives a portion of input data from a database. The generic database application can communicate with the database using a variety of different database schemas. The generic database application of the computer system infers a portion of ORM metadata associated with the received input data. The computer system accesses a generic ORM query where the ORM query is configured to provide mapping information to map the input data into a graph of objects according to the database object properties included in the ORM metadata. The computer system maps the input data into a graph of objects using the database object properties included in the ORM metadata and displays an ORM object view which includes the graph of objects.

Abstract: The present invention extends to methods, systems, and computer program products for accessing and manipulating data in a data flow graph. A data flow graph includes one more transforms for transforming data from one or more data stores into different formats accessible to clients. Transforms can be configured to join and split data from the same or different data stores. A metadata tree logically represents the data flow graph including locations that provide output from transforms of the data flow graph. The locations can be referenced by clients to access transformed outputs. Clients can register dependencies on data at various locations and can request evaluation of the data in response to data changes at a corresponding data store. Clients can also request data changes be propagated back through the data flow graph to one or more data stores and implemented at the one or more data stores.