A method and system for eliminating the redundant allocation and deallocation of special data on disk, wherein the redundant allocation and deallocation of special data on disk is eliminated by providing an innovate technique for specially allocating special data of a storage system. Specially allocated data is data that is pre-allocated on disk and stored in memory of the storage system. “Special data” may include any pre-decided data, one or more portions of data that exceed a pre-defined sharing threshold, and/or one or more portions of data that have been identified by a user as special. For example, in some embodiments, a zero-filled data block is specially allocated by a storage system. As another example, in some embodiments, a data block whose contents correspond to a particular type document header is specially allocated.

Multiple data paths may be available to a data management system for transferring data between a primary storage device and a secondary storage device. The data management system may be able to gain operational advantages by performing load balancing across the multiple data paths. The system may use application layer characteristics of the data for transferring from a primary storage to a backup storage during data backup operation, and correspondingly from a secondary or backup storage system to a primary storage system during restoration.

One example method includes optimizing client-side deduplication. When backing up a client, an overwrite ratio is determined based on a size of actual changes made to a volume and a size indicated by changes in a change log. Client-side deduplication is enabled or disabled based on a value of the overwrite ratio.

Multi-site distributed storage systems and computer-implemented methods are described for providing an automatic unplanned failover (AUFO) feature to guarantee non-disruptive operations (e.g., operations of business enterprise applications, operations of software application) even in the presence of failures including, but not limited to, network disconnection between multiple data centers and failures of a data center or cluster.

Described in detail herein are systems and methods for single instancing blocks of data in a data storage system. For example, the data storage system may include multiple computing devices (e.g., client computing devices) that store primary data. The data storage system may also include a secondary storage computing device, a single instance database, and one or more storage devices that store copies of the primary data (e.g., secondary copies, tertiary copies, etc.). The secondary storage computing device receives blocks of data from the computing devices and accesses the single instance database to determine whether the blocks of data are unique (meaning that no instances of the blocks of data are stored on the storage devices). If a block of data is unique, the single instance database stores it on a storage device. If not, the secondary storage computing device can avoid storing the block of data on the storage devices.

Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.

A computer-implemented method for database management is provided. The method comprises: receiving, from a client device, first data to be stored in a database system that comprises first data storage configured to store a data table and a deletion history table; storing the first data in second data storage that is external to the database system and that is in communication with the database system via a network; obtaining a link that enables access, via the network, to the first data stored in the second data storage; storing the link in the data table; and performing a deletion operation of the first data, in response to a request from the client device to delete the first data from the database system, wherein the deletion operation comprises: deleting the link from the data table without deleting the first data from the second data storage; and storing the link in the deletion history table with a timestamp corresponding to a point in time when the link is deleted from the data table.

The disclosed embodiments disclose techniques for journaling data received in a cloud-based distributed computing environment (CBDCE). Multiple services simultaneously execute on the CBDCE compute nodes, with each service comprising multiple service instances that simultaneously execute on multiple, distinct compute nodes of the CBDCE. The CBDCE includes a distributed database that enables coordination between the service instances of services that execute in the CBDCE; this distributed database also includes multiple distributed database instances that simultaneously executing on multiple different CBDCE compute nodes. During operation, a service instance executing on one of these compute nodes receives a client request. The service instance submits this client request to a distributed database instance and, in parallel, also submits the client request and its associated user data to a distributed journaling service.

Methods, computer program products, and computer systems for the management of data references in an efficient and effective manner are disclosed. Such methods, computer program products, and computer systems include receiving a change tracking stream at the computer system, identifying a data object group, and performing a deduplication management operation on the data object group. The change tracking stream is received from a client computing system. The change tracking stream identifies one or more changes made to a plurality of data objects of the client computing system. The identifying is based, at least in part, on at least a portion of the change tracking stream. The data object group represents the plurality of data objects.

For restoring data, a system with uninterrupted block-based restore has a hybrid container. The hybrid container has an operational buffer and a virtual container unit. The system receives blocks of data from a target device into the hybrid container and sends the blocks of data from the hybrid container to a destination device for a restore session. The system writes information about the blocks of data into one or more virtual containers. If there is an abort of the restore session, the system freezes state of the hybrid container and the virtual container(s). For a next restore session that resumes from where the aborted restore session stopped, the system resumes receiving blocks of data from the target device into the hybrid container and sends only leftover blocks of data to the destination device in accordance with the information in the virtual container(s).