Abstract: Among other things, there are two or more data sets. Each of the data sets contains data that can be interpreted as records each having data values for data fields. Each of the data sets contains at least some data that is related to data in at least one of the other data sets. The data in different data sets is organized or expressed possibly differently. Each of the data sets is susceptible to a definition of a key for the records of the data set. The data sets are characterized by repetitions of at least one of (a) records, (b) portions of keys, or (c) instances of values for data fields. Information about at least one of the repetitions is provided to a user.

Abstract: Among other things, a machine-based method comprises receiving an application specification comprising one or more algorithms. Each algorithm is not necessarily suitable for concurrent execution on multiple nodes in parallel. One or more different object classes are grouped into one or more groups, each being appropriate for executing the one or more algorithms of the application specification. The executing involves data that is available in objects of the object classes. A user is enabled to code an algorithm of the one or more algorithms for one group in a single threaded environment without regard to concurrent execution of the algorithm on multiple nodes in parallel. An copy of the coded algorithm is distributed to each of the multiple nodes, without needing additional coding. The coded algorithm is caused to be executed on each node in association with at least one instance of a group independently of and in parallel to executing the other copies of the coded algorithm on the other nodes.

Abstract: Among other things, a machine-based method is described. The method comprises recording object classes of an object model, producing an object representation for data of two or more data sources based on a mapping of data formats of the data sources to the object classes of the object model, and producing mapped data from the data sources. The mapped data is available in objects of the object classes and is comparable in the object representation. At least two of the data sources have different data formats.

Abstract: Among other things, a node is enabled to participate, with other nodes, in forming and using transport layer features in a communication network, the transport layer features being extensible to support ten million or more simultaneous reliable conversations between or among applications running on respective participant nodes.

Abstract: Among other things, there are two or more data sets. Each of the data sets contains data that can be interpreted as records each having data values for data fields. Each of the data sets contains at least some data that is related to data in at least one of the other data sets. The data in different data sets is organized or expressed possibly differently. Each of the data sets is susceptible to a definition of a key for the records of the data set. The data sets are characterized by repetitions of at least one of (a) records, (b) portions of keys, or (c) instances of values for data fields. Information about at least one of the repetitions is provided to a user.

Abstract: Among other things, a machine-based method is described. The method comprises recording object classes of an object model, producing an object representation for data of two or more data sources based on a mapping of data formats of the data sources to the object classes of the object model, and producing mapped data from the data sources. The mapped data is available in objects of the object classes and is comparable in the object representation. At least two of the data sources have different data formats.

Abstract: Among other things, a node is enabled to participate, with other nodes, in forming and using transport layer features in a communication network, the transport layer features being extensible to support ten million or more simultaneous reliable conversations between or among applications running on respective participant nodes.

Abstract: Among other things, there are two or more data sets. Each of the data sets contains data that can be interpreted as records each having data values for data fields. Each of the data sets contains at least some data that is related to data in at least one of the other data sets. The data in different data sets is organized or expressed possibly differently. Each of the data sets is susceptible to a definition of a key for the records of the data set. The data sets are characterized by repetitions of at least one of (a) records, (b) portions of keys, or (c) instances of values for data fields. Information about at least one of the repetitions is provided to a user.

Abstract: Among other things, requests are received for tasks to be performed in a database. The tasks include tasks that will cause changes in data of the database and other tasks that must be executed on data in the database that is consistent time-wise. At least some of the data that will be changed by the change-causing tasks comprises data that must remain time-wise consistent for the other tasks. The other tasks are executed in the database while the change-causing tasks are also being executed in the database, without requiring a replication or reconfiguration of the database.

Abstract: Data is stored persistently. At least two different items of the data are stored in two different non-conflicting regions or two different physical clusters. A relationship is maintained between the two different items of data. The relationship enables a process to reach any one of the data items from the other data item. Consistency of the relationship is maintained notwithstanding updates of either or both of the items.

Abstract: Among other things, a node is enabled to participate, with other nodes, in forming and using transport layer features in a communication network, the transport layer features being extensible to support ten million or more simultaneous reliable conversations between or among applications running on respective participant nodes.

Abstract: A database is maintained that stores data persistently. Tasks are accepted from task sources. At least some of the tasks have competing requirements for use of regions of the database. Each of the regions includes data that is all either locked or not locked for writing at a given time. Each of the regions is associated with an available processor. For each of the tasks, jobs are defined each of which requires write access to regions that are to be accessed by no more than one of the processors. Jobs are distributed for concurrent execution by the associated processors.

Abstract: Among other things, a machine-based method is described. The method comprises recording object classes of an object model, producing an object representation for data of two or more data sources based on a mapping of data formats of the data sources to the object classes of the object model, and producing mapped data from the data sources. The mapped data is available in objects of the object classes and is comparable in the object representation. At least two of the data sources have different data formats.

Abstract: Among other things, a machine-based method is described. The method comprises recording object classes of an object model, producing an object representation for data of two or more data sources based on a mapping of data formats of the data sources to the object classes of the object model, and producing mapped data from the data sources. The mapped data is available in objects of the object classes and is comparable in the object representation. At least two of the data sources have different data formats.

Abstract: A database is maintained that stores data persistently. Tasks are accepted from task sources. At least some of the tasks have competing requirements for use of regions of the database. Each of the regions includes data that is all either locked or not locked for writing at a given time. Each of the regions is associated with an available processor. For each of the tasks, jobs are defined each of which requires write access to regions that are to be accessed by no more than one of the processors. Jobs are distributed for concurrent execution by the associated processors.

Abstract: A database is maintained that stores data persistently. Tasks are accepted from task sources. At least some of the tasks have competing requirements for use of regions of the database. Each of the regions includes data that is all either locked or not locked for writing at a given time. Each of the regions is associated with an available processor. For each of the tasks, jobs are defined each of which requires write access to regions that are to be accessed by no more than one of the processors. Jobs are distributed for concurrent execution by the associated processors.

Abstract: Among other things, a node is enabled to participate, with other nodes, in forming and using transport layer features in a communication network, the transport layer features being extensible to support ten million or more simultaneous reliable conversations between or among applications running on respective participant nodes.

Abstract: Among other things, a node is enabled to participate, with other nodes, in forming and using transport layer features in a communication network, the transport layer features being extensible to support ten million or more simultaneous reliable conversations between or among applications running on respective participant nodes.

Abstract: Among other things, a machine-based method comprises receiving an application specification comprising one or more algorithms. Each algorithm is not necessarily suitable for concurrent execution on multiple nodes in parallel. One or more different object classes are grouped into one or more groups, each being appropriate for executing the one or more algorithms of the application specification. The executing involves data that is available in objects of the object classes. A user is enabled to code an algorithm of the one or more algorithms for one group in a single threaded environment without regard to concurrent execution of the algorithm on multiple nodes in parallel. An copy of the coded algorithm is distributed to each of the multiple nodes, without needing additional coding. The coded algorithm is caused to be executed on each node in association with at least one instance of a group independently of and in parallel to executing the other copies of the coded algorithm on the other nodes.

Abstract: Among other things, requests are received for tasks to be performed in a database. The tasks include tasks that will cause changes in data of the database and other tasks that must be executed on data in the database that is consistent time-wise. At least some of the data that will be changed by the change-causing tasks comprises data that must remain time-wise consistent for the other tasks. The other tasks are executed in the database while the change-causing tasks are also being executed in the database, without requiring a replication or reconfiguration of the database.