A method, apparatus, and system for policy driven data placement and information lifecycle management in a database management system are provided. A user or database application can specify declarative policies that define the movement and transformation of stored database objects. The policies are associated with a database object and may also be inherited. A policy defines, for a database object, an archiving action to be taken, a scope, and a condition before the archiving action is triggered. Archiving actions may include compression, data movement, table clustering, and other actions to place the database object into an appropriate storage tier for a lifecycle phase of the database object. Conditions based on access statistics can be specified at the row level and may use segment or block level heatmaps. Policy evaluation occurs periodically in the background, with actions queued as tasks for a task scheduler.

Provided is a backup system including a storage system and a backup server, in which the backup server includes a ledger for managing a copy number and a backup acquisition date and time for each backup image, a data volume that stores data accessed by a business server, a backup image volume that stores a plurality of backup images at different time points of the data volume, an access volume having a volume ID for accessing the backup image from the backup server, and a data protection area including at least one volume having an internal volume ID instead of the volume ID for accessing from the backup server are configured in the storage system, and the backup image stored in the data protection area and the access volume are associated, and the backup image in the data protection area is provided to the backup server.

Provided are a data archiving method and apparatus capable of providing a remote near-line data archiving function by receiving remote function invoking from a target system in which data is stored, providing the target system with a first function for archiving, in a storage system, at least some of the data stored in the target system over a network in response to the remote function invoking, and providing the target system with a second function for the query of the data archived in the storage system over the network.

In an approach to longevity management of social network data, a computer detects a posting of a social artifact by a first user of a social network. A computer stores the social artifact with associated identification information. A computer stores activity associated with the social artifact by one or more other users. A computer detects a status change in an account associated with the first user, wherein the status change indicates the first user is not active in the social network. In response to detecting the status change, a computer determines a second user from the one or more other users to which to transfer the social artifact based on the social artifact, the associated identification information, and the activity associated with the social artifact by the one or more other users. A computer transfers the social artifact to an account associated with the second user on the social network.

Described are methods, systems and computer readable media for dynamic updating of query result displays.

The cloud hybrid application storage management system spans local data center and cloud-based storage and provides a unified view of content and administration throughout an enterprise. The system manages synchronization of storage locations, ensuring that files are replicated, uniquely identified, and protected against corruption. The system ingests digital media assets and creates instances of the assets with their own identification and rights and houses the identification and relationships in a CAR (Central Asset Registry). The system tracks the different instances of the assets in multiple storage locations using the CAR, which is a central asset registry that ties together disparate digital asset management repository systems (DAMs) and cloud-based storage archives in which the instances reside. While the invention treats and manages multiple files/instances independently, the CAR identifies them as related to each other.

Techniques are described for sharing prepopulated container image caches among container execution environments to improve the performance of container launches. The container images used to prepopulate such a cache at a computing device supporting one or more container execution environments can include various container images that are used as the basis for a wide range of user-created containers such as, for example, container images representing popular operating system distributions, database servers, web-application frameworks, and so forth. Existing systems typically obtain these container images as needed at runtime when launching containers (for example, from a container registry or other external source), often incurring significant overhead in the container launch process. The use of a prepopulated container image cache can significantly improve the performance of container launches by making such commonly used container images available to container execution environments running at a computing device ahead of time.

Described are methods, systems and computer readable media for performance logging of complex query operations.

Techniques for enabling user search of content stored in a file archive include providing a search interface comprising a search rules portion and an action rules portion, receiving a file archive search criterion comprising at least one search rule, and searching the file archive using the search criterion. The techniques also include generating a set of files filtered using the search criterion and performing an action specified in the action rules portion on a file included in the set of files.

A method and system for executing database queries in parallel using a shared metadata store. The metadata store may reside on a master node, where the master node is the root node in a tree. The master node may distribute query plans and query metadata to other nodes in the cluster. These additional nodes may request additional metadata from each other or the master nodes as necessary.