Abstract: Content categories are identified based on content provided by a server associated with an enterprise content management system. Using the relationship database, a content category is identified based on content associated with a client associated with a user, the content associated with the client associated with the user including content accessed by the user. A document associated with the content category is identified. A message is sent from the server to the client associated with the user to suggest to the user the document associated with the content category.

Abstract: Content categories are identified based on content provided by a server associated with an enterprise content management system. Using the relationship database, a content category is identified based on content associated with a client associated with a user, the content associated with the client associated with the user including content accessed by the user. A document associated with the content category is identified. A message is sent from the server to the client associated with the user to suggest to the user the document associated with the content category.

Abstract: Content categories are identified based on content provided by a server associated with an enterprise content management system. Using the relationship database, a content category is identified based on content associated with a client associated with a user, the content associated with the client associated with the user including content accessed by the user. A document associated with the content category is identified. A message is sent from the server to the client associated with the user to suggest to the user the document associated with the content category.

Abstract: Content categories are identified based on content provided by a server associated with an enterprise content management system. Using the relationship database, a content category is identified based on content associated with a client associated with a user, the content associated with the client associated with the user including content accessed by the user. A document associated with the content category is identified. A message is sent from the server to the client associated with the user to suggest to the user the document associated with the content category.

Abstract: Content categories are identified based on content provided by a server associated with an enterprise content management system. Using the relationship database, a content category is identified based on content associated with a client associated with a user, the content associated with the client associated with the user including content accessed by the user. A document associated with the content category is identified. A message is sent from the server to the client associated with the user to suggest to the user the document associated with the content category.

Abstract: Cache data analysis for enterprise content management systems is described. A content category is identified based on content provided by a cache server associated with an enterprise content management system. A determination is made whether content associated with the content category is cached by the cache server. The content associated with the content category is requested by the cache server if the content associated with the content category is not cached by the cache server. The content associated with the content category is cached by the cache server.

Abstract: Cache data analysis for enterprise content management systems is described. A content category is identified based on content provided by a cache server associated with an enterprise content management system. A determination is made whether content associated with the content category is cached by the cache server. The content associated with the content category is requested by the cache server if the content associated with the content category is not cached by the cache server. The content associated with the content category is cached by the cache server.

Abstract: Cache data analysis for enterprise content management systems is described. A content category is identified based on content provided by a cache server associated with an enterprise content management system. A determination is made whether content associated with the content category is cached by the cache server. The content associated with the content category is requested by the cache server if the content associated with the content category is not cached by the cache server. The content associated with the content category is cached by the cache server.

Abstract: Cache data analysis for enterprise content management systems is described. A content category is identified based on content provided by a cache server associated with an enterprise content management system. A determination is made whether content associated with the content category is cached by the cache server. The content associated with the content category is requested by the cache server if the content associated with the content category is not cached by the cache server. The content associated with the content category is cached by the cache server.

Abstract: Cache data analysis for enterprise content management systems is described. A content category is identified based on content provided by a cache server associated with an enterprise content management system. A determination is made whether content associated with the content category is cached by the cache server. The content associated with the content category is requested by the cache server if the content associated with the content category is not cached by the cache server. The content associated with the content category is cached by the cache server.

Abstract: A system and method for Java object storage and retrieval in a non-volatile all flash memory database. Bean annotations define the attributes of objects and object classes that are created using a Java compiler in an all flash Java runtime environment. Object indexes are created based upon these attributes, and a Java object query language using the indexes is employed to locate objects in the all flash memory database. A new transactional model is provided for managing objects and memory in the all flash memory database, and a new garbage collector deletes objects and reclaims memory.

Abstract: On-demand aggregated logging for distributed systems is described. An identification of a logging condition is received via a first user interface. The logging condition is sent to multiple logging elements, wherein each of the multiple logging elements is executing on a corresponding one of multiple distributed systems components. A logging element determines whether a local runtime condition matches the logging condition. The logging element sends a local log associated with the local runtime condition to an aggregating logger, wherein the local log is supplemented with information that identifies the logging condition, in response to a determination that the local runtime condition matches the logging condition. The aggregating logger creates an aggregated log based on the local log and the supplemented information. The aggregated log is output via a second user interface to enable resolution of a problem associated with the multiple distributed systems components.

Abstract: A system and method for Java object storage and retrieval in a non-volatile all flash memory database. Bean annotations define the attributes of objects and object classes that are created using a Java compiler in an all flash Java runtime environment. Object indexes are created based upon these attributes, and a Java object query language using the indexes is employed to locate objects in the all flash memory database. A new transactional model is provided for managing objects and memory in the all flash memory database, and a new garbage collector deletes objects and reclaims memory.