Abstract: Architecture that eliminates the need for on-disk full backups of data retaining only changes that have occurred, in a separate table. Thus, the architecture provides for incremental recovery of incremental changes in a relational database (e.g., SQL). The architecture provides improved recovery time and recovery point objectives. By using the incremental capture of changed data (e.g., in an XML format), the capability is provided to capture schema changes, query the incremental change data and efficiently restore user data to an earlier point-in-time state. Changes (e.g., insert, update and delete operations) are tracked (e.g., continuously) by a set of triggers and the incrementally captured changed rows are inserted in a data capture table (a differential change “delta” table) in a human-readable format (e.g., XML). Rollback is also provided.

Abstract: Architecture that eliminates the need for on-disk full backups of data retaining only changes that have occurred, in a separate table. Thus, the architecture provides for incremental recovery of incremental changes in a relational database (e.g., SQL). The architecture provides improved recovery time and recovery point objectives. By using the incremental capture of changed data (e.g., in an XML format), the capability is provided to capture schema changes, query the incremental change data and efficiently restore user data to an earlier point-in-time state. Changes (e.g., insert, update and delete operations) are tracked (e.g., continuously) by a set of triggers and the incrementally captured changed rows are inserted in a data capture table (a differential change “delta” table) in a human-readable format (e.g., XML). Rollback is also provided.

Abstract: Architecture that facilitates the restoration of a cluster database in a scalable way using backups (e.g., SQL database backups) and a partition rebuild mechanism to achieve a high level of partition level data consistency, even when restore fails on individual machines and/or machine failure occurs. The architecture restores replicas of the partitions in consideration that the backups may be created at different points and at different times. Optimized parallelism is achieved in restoring each database machine using local backups, which eliminates cross-machine network traffic. Thus, fast recovery of the distributed database can be accomplished on the order of hours over thousands of machines and terabytes of data.

Abstract: Storing and querying XML data in a primary table or document utilizes an index of XML data and includes creating a primary table structure, creating a primary XML index commensurate with the primary table structure, populating the primary table and the primary XML index, and running a query on the XML data in a primary table by utilizing the XML index. The XML index can be implemented as a node table. The node table may have a B+-tree structure and be populated by shredding the XML values in the primary table. The XML data may be stored as binary large objects in an XML column of the primary table. Secondary XML indexes may be created to assist in the search and retrieval of XML data stored in the primary table. Both the primary XML index and the secondary XML index tables may be created using data definition language statements.

Abstract: A method and system for transforming a query tree that includes more than one aggregator. The method includes identifying a first aggregator in the query tree, identifying a second aggregator that is located below the first aggregator in the query tree, and merging the second aggregator with the first aggregator to form a merged aggregator.

Abstract: An improved type inference may be calculated for a path expression that may be classified into a series of input expressions followed by steps. For each such series, the inference may be calculated based on input including a type for the input expression, an axis for the step, and a node test for the step. The cardinality of the input expression type is preserved for the calculation of the step type. Also, a set of one or more matching node types may be identified within the type repository. These matching node types are node types within the axis of the step that match the node test of the step. These matching node types are identified without calculating the full content type implied by the axis. Avoiding the calculation of the full content type of the axis may reduce the processing time required to perform the inference.