Rubrik, Inc.

International Business Machines Corporation

Pin Zhou

Prasenjit Sarkar

Nagapramod S Mandagere

Sandeep Madhav Uttamchandani

Kavita Chavda

Seshashayee Sankarshana Murthy

Tarun Thakur

Maohua Lu

Ajaykrishna Raghavan

Rohit Shekhar

Hyo Jun Kim

Ramani Ranjan Routray

Robert Michael Rees

Mickey Iqbal

Wayne Curtis Hineman

Rajath Subramanyam

Brian Cho

Veera W Deenadhayalan

Nohhyun Park

Gaurav Khandelwal

Brian Yin

Steven Robert Hetzler

Mario Blaum

Abhishek Dharmapurikar

Sandeep M Uttamachandani

Binny Sher Gill

Windsor Wee Sun Hsu

Wendy Ann Belluomini

Mark Davis Smith

David Allan Pease

Mark Andrew Smith

Mohit Saxena

Anurag Sharma

Jiangbin Luo

Guilherme Vale Ferreira Menezes

Neville Carvalho

Hyojun Kim

Xifeng Yan

Abhishek Dharmaprikar

Eric W Davis Rozier

Described herein is a system that restores a database by processing a portion of the database. The system restores the database to a previous state at a particular time by reverting data entries that have changed since the time to their initial values before the change. Data entries that have changed after the restore time are identified. For the data entries that have changed after the restore time, their initial values before the change are determined from various sources. The system determines a database version that is created most recently before the restore time. The system additionally identifies changes to the database between the restore time and when the database version is created. The initial values can be determined from either the database version or the changes made to the database between the restore time and when the database version is created.

Partial database restoration

A object data backup and restore method and system include receiving a request to restore a target object to a first point-in-time version; identifying a first snapshot of the cluster corresponding to the first point-in-time version; generating a second snapshot of the cluster upon receiving the request to restore the target object; determining data changes associated with the target object based on the first snapshot and second snapshot; scanning all objects associated with the cluster to determine one or more additional objects that are affected by restoring the target object due to object dependencies defined by a cluster configuration; generating a relationship graph for the one or more additional objects and the target object; and restoring the target object based on the data changes, the first snapshot and the relationship graph.

Object data backup and recovery in clusters managing containerized applications

Embodiments disclosed herein provide systems, methods, and computer readable media for data lineage based multi-data store recovery. In a particular embodiment, a method provides identifying first data in a first table of a plurality of tables stored in a plurality of data stores and restoring the first data to a first correct version of the first data in a prior version of the first table. The method further provides identifying a second table of the plurality of tables that descends from the first table and includes second descendent data that stems from the first data. The method also provides restoring the second descendent data to a second correct version of the second descendent data in a prior version of the second table.

Data lineage based multi-data store recovery

Embodiments disclosed herein provide systems, methods, and computer readable media for sub-cluster recovery in a data storage environment having a plurality of storage nodes. In a particular embodiment, the method provides scanning data items in the plurality of nodes. While scanning, the method further provides indexing the data items into an index of a plurality of partition groups. Each partition group includes data items owned by a particular one of the plurality of storage nodes. The method then provides storing the index.

Sub-cluster recovery using a partition group index

In some examples, a cluster protection system comprises at least one processor and a memory storing instructions which, when executed by the at least one processor, cause the system to perform operations comprising identifying a target cluster or an object in a container management framework, identifying application data and metadata associated with the target cluster or the object, generating a first snapshot of the target cluster or the object, the first snapshot including at least the metadata, storing the first snapshot in offsite cloud storage, generating a second snapshot of the target cluster, the second snapshot including at least the application data, and storing the second snapshot in a persistent volume in onsite storage.

Data backup in container management frameworks

Embodiments disclosed herein provide systems, methods, and computer readable media for infinite versioning by automatic coalescing. In a particular embodiment, a method provides determining an age range for a plurality of data versions stored in a secondary data repository and identifying first data versions of the plurality of data versions that are within the age range. The method further provides determining a compaction ratio for the first data versions and compacting the first data versions based on the compaction ratio.

Infinite versioning by automatic coalescing

The technology disclosed herein enables the restoration of a database version across cloud environments. In a particular embodiment, a method provides receiving, in a second cloud environment from a first cloud environment, first metadata describing a first data version stored in the first cloud environment. The first data version includes first data items and the first metadata. After receiving the first metadata, the method provides receiving, in the second cloud environment, an instruction to restore the first data items to the second cloud environment. In response to the instruction, the method provides restoring the first data items to the second cloud environment using the first metadata.

Database restoration across cloud environments

Systems and methods for shard consistency in a clustered database are described. The system identifies an addition of a first shard to a clustered database on a source storage platform. The clustered database includes at least two shards and the first shard includes a first node. The system communicates a first node agent to the first node. The node agent being is configured to execute on the first node to extract a data image and an operation log at the source storage platform and stream the data image and the operation log to the secondary storage platform. The system versions a first version of the clustered database. The versioning includes storing the data image and operation log for the first node at the second storage platform. The timestamp associated with the first shard is different than the timestamp for other shards in the clustered database.

Systems and methods for shard consistency in a clustered database

The method disclosed is for instantiating a second cluster based on a first cluster. For at least one node of a second plurality of nodes, generating per node data based on mappings between a plurality of partition groups and a first plurality of nodes, the first plurality of nodes corresponding to the first cluster. The method further discloses identifying data items included in the plurality of partition groups based on the mappings between the plurality of partition groups and the first plurality of nodes. The method further discloses each partition group corresponding to a node of the first plurality of nodes and comprising a subset of data items stored in the node. The method further discloses loading the data items included in the plurality of partition groups onto the second plurality of nodes, the second plurality of nodes corresponding to the second cluster.

The method disclosed includes scanning data items stored in the first plurality of nodes of a first cluster. While scanning, creating a partition group index indexing the data items into a plurality of partition groups. Each partition group corresponds to a node of the first plurality of nodes and comprises a subset of data items stored in the node. Storing the index. Instantiating a second cluster, comprising generating per node data, for each node of a second plurality of nodes, based on mappings between the partition groups and the first plurality of nodes. Identifying the data items included in the partition groups according to the partition group index and loading the data items included in the partition groups onto the second plurality of nodes.

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San Jose, CA, United States of America

Pin Zhou