Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: Embodiments of distributed storage systems are disclosed herein. Certain embodiments maintain statistics associated with storage locations within the distributed storage system at servers within the distributed storage systems. The statistics maintained at each server may be particularized to that server with respect to each storage location. These statistics may be utilized to predict access costs associated with requests for data (e.g., read or write requests) within the distributed storage system. The predicted access costs are, in turn, used to select a storage location in servicing the data access requests increasing computer performance and efficiency at least by decreasing access involved with requests for such data.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: Responsive to a request to retrieve or store a file, a transformation pipeline may be created to efficiently transform file data one unit at a time in memory. The transformation pipeline includes a sequence of transformation streams, each containing a write method, a read method, and a transformation to be applied. The write method moves a unit of data, for instance, from a memory buffer into an associated stream. The read method reads the unit of data from the stream, calls an associated transformation, and passes the unit of data thus transformed to the next stream or a destination. This process is repeated until all desired and/or required transformations such as compression, encryption, tamper protection, conversion, etc. are applied to the unit of data.

Abstract: An entity modeling system integrated with a low-code application development platform may have a web/mobile-based user interface that can run in a browser environment on user devices ranging from desktop computers to smart phones. Users such as a subject matter expert may access an entity model designer tool of the system to model an entity. Responsive to user interaction with an entity composition function, the system may access a data store over a network and generate a view including a collection of entity building block(s) retrieved from the data store. Responsive to the user selecting a first entity building block from the collection to add to the entity, the system may automatically extend the entity to include settings of the first entity building block. The settings may include at least one of a property, permission, action, behavior, or resource to the entity.

Abstract: Responsive to a request to retrieve or store a file, a transformation pipeline may be created to efficiently transform file data one unit at a time in memory. The transformation pipeline includes a sequence of transformation streams, each containing a write method, a read method, and a transformation to be applied. The write method moves a unit of data, for instance, from a memory buffer into an associated stream. The read method reads the unit of data from the stream, calls an associated transformation, and passes the unit of data thus transformed to the next stream or a destination. This process is repeated until all desired and/or required transformations such as compression, encryption, tamper protection, conversion, etc. are applied to the unit of data.

Abstract: Embodiments of distributed storage systems are disclosed herein. Certain embodiments maintain statistics associated with storage locations within the distributed storage system at servers within the distributed storage systems. The statistics maintained at each server may be particularized to that server with respect to each storage location. These statistics may be utilized to predict access costs associated with requests for data (e.g., read or write requests) within the distributed storage system. The predicted access costs are, in turn, used to select a storage location in servicing the data access requests increasing computer performance and efficiency at least by decreasing access involved with requests for such data.