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Thomas Fischer

Romans Kasperovics

Marcus Paradies

Cornelia Kinder

Jan Bross

Hinnerk Gildhoff

Christoph Weyerhaeuser

Tobias Mindnich

Bjoern Panter

Dominik Held

Markus Fath

Juergen Mahler

Mahadevan Venkata

Bernd Sieren

A method for performing a path finding operation in graph data stored in a database is provided. The method may include receiving, from a client, a request to perform a weighted path operation on at least portion of the graph data. The portion of the graph data may correspond to a graph. The request may specify attributes associated with vertices and/or edges included in the graph. In response to the request, the weighted path operation may be performed by at least identifying a shortest path between two endpoints in the graph. The shortest path may minimize the one or more attributes of vertices and/or edges included in the shortest path. Related systems and articles of manufacture, including computer program products, are also provided.

Extended path finding operations on graph data

A method for executing a graph algorithm is provided. The method may include responding to a request from a client to execute a graph algorithm on graph data stored in a database by determining data required to execute the graph algorithm. In response to determining that a first portion of the data required to execute the graph algorithm is absent from an existing adjacency structure that includes a second portion of the data required to execute the graph algorithm, the existing adjacency structure may be modified to include the first portion of data. The graph algorithm may be executed based on the modified adjacency structure. The execution of the graph algorithm may include querying, based on the modified adjacency structure, the graph data stored in the database. Related systems and articles of manufacture, including computer program products, are also provided.

Adaptable adjacency structure for querying graph data

A method for executing a graph algorithm may include responding to a request from a client to execute a graph algorithm on graph data stored in a database by determining data required to execute the graph algorithm. In response to determining that a first portion of the data required to execute the graph algorithm is absent from an existing adjacency structure that includes a second portion of the data required to execute the graph algorithm, the existing adjacency structure may be modified to include the first portion of data. The graph algorithm may be executed based on the modified adjacency structure. The execution of the graph algorithm may include querying, based on the modified adjacency structure, the graph data stored in the database. Related systems and articles of manufacture, including computer program products, are also provided.

Graph data derivatives

A method for performing text searches on graph data stored in a database is provided. The method may include receiving, from a client, a request to perform a text search to locate a target string in the graph data stored in the database. The request may be in accordance with a declarative graph query configured to query the graph data stored in the database. The response to the request may include performing the text search to locate, in the graph data stored in the database, one or more records of strings that are exact matches, approximate matches, and/or linguistic matches for the target string. Related systems and articles of manufacture, including computer program products, are also provided.

Text searches on graph data

A system for processing graph-modeled data in a relational database is provided. The system can include at least one data processor and at least one memory storing instructions that are executed by the at least one data processor. Executing the instructions can result in operations comprising: receiving a request to execute a graph algorithm operating on graph-modeled data stored at a relational database; and executing the graph algorithm within the relational database, the executing comprising use of an adjacency structure within the relational database. Related methods and articles of manufacture, including computer program products, are also provided.

Adjacency structures for executing graph algorithms in a relational database

A system for processing graph-modeled data in a relational database is provided. In some implementations, the system performs operations comprising: receiving, from a first user, a request to define a graph algorithm operating on a graph workspace, the graph workspace comprising at least a portion of graph-modeled data stored at a relational database; applying a first security rule associated with the relational database, the applying comprising determining whether the first user has a privilege to define the graph algorithm operating on the graph workspace; and storing the graph algorithm at the relational database, when the first user is determined to have the privilege to define the graph algorithm operating on the graph workspace. Related methods and articles of manufacture, including computer program products, are also provided.

Graph-modeled data processing in a relational database

Based on received input, a vertex table of the database layer and a vertex key column in the vertex table can be identified. The vertex key column defines vertices of a graph representation. Also based on the received input, an edge table of the database layer, an edge key column in the edge table, a source column in the edge table, and a target column in the edge table can be identified. The source column and target column define relationships between vertices of the plurality of vertices. Within a graph workspace object, graph relationships linking the vertices defined by the vertex key column via edges defined by the source column and target column in the edge table can be assigned, and the graph workspace can be generated in a higher level programming layer based on the graph workspace object.

Extensions of structured query language for database-native support of graph data

A computer system determines a first criticality relating to frequency of execution of computer programs, a second criticality relating to frequency of execution of transactions, a third criticality relating to a number of users who execute the transactions, a fourth criticality relating to programs that modify the database tables having a large change in data, and a fifth criticality relating to the amount to time that each computer program is executed and the amount of time that each transaction is executed. The system determines intersections among the criticalities, and assigns a weighted value to each of the intersections. The system determines an overall criticality for a particular computer program or a particular transaction. The overall criticality is a function of the number of intersections in which the particular computer program or the particular transaction appears and the weighted values assigned to the intersections.

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Sandhausen, Germany

Thomas Fischer