Tesora, Inc.

Parelastic Corporation

Verizon Patent and Licensing Inc.

Mrithyunjaya Annapragada

Benjamin A Rousseau

Duk Loi

Douglas A Shelley

Morgan Jones

Kenneth Rugg

Andrew Bramley

Peter Stachowski

A device receives a request for a second artifact, where the request identifies a first artifact that is different than the second artifact. The device obtains at least one transformation for transforming the first artifact into the second artifact, and uses the obtained at least one transformation to transform the first artifact into the second artifact. The device launches or instantiate a compute resource or a logical disk volume using the second artifact, where the compute resource includes one of a virtual machine, a baremetal, or a container. The first artifact and the second artifact each includes an image or a snapshot.

Artifact transformation in network devices

An elastic parallel database system where data distribution is container- and container-context based. Container Based Tables are defined and Container Member Tables achieve co-location of data as needed. A polymorphic key may also establish polymorphic key relationships between rows in one table and rows in many other possible tables.

Advancements in data distribution methods and referential integrity

An elastic parallel database system where metadata is specified out-of-band during database operations via a set of augmentation rules. The rules are used to augment or modify commands received, and indicate whether they are to be used for specific connections on which they are received, for all client connections, or some other scope.

Extensions to generational data distribution methods

A database management system implemented in a cloud computing environment. Operational nodes are assigned as controller-nodes, compute-nodes or storage-nodes. The number of operational nodes, and their assignment as compute-nodes or storage-nodes can vary. Queries specify tables, with each such table assigned to a respective group of storage nodes. The number of operational nodes executing a given query may change by (a) changing the compute-nodegroup associated with a connection, or (b) adding or removing nodes from the compute-nodegroup; and/or distributing data from the tables among the nodes in a storage nodegroup. State information is maintained for each client connection, such that steps are executed assuming that the state exists. State changes are recorded during step execution for a given connection, so that subsequent steps from the same connection are executed with the state as left by a prior step, and so that subsequent queries on the same connection are executed with the state as left by the prior query.

Improvements to query execution in a parallel elastic database management system

Platform agnostic resource provisioning

Dynamic rules based query rewriting engine

Out-of-band specification of metadata during database operations

Redistribution reduction in EPRDBMS

Smart distributed transactions and multiply distributed tables

Mechanism for co-located data placement in a parallel elastic database management system

A database management system implemented in a cloud computing environment. Operational nodes are assigned as groups of controller-nodes, compute-nodes or storage-nodes. Assignments as compute-nodes or storage-nodes vary during execution of queries. Queries specify tables for an associated database operation, and respective storage nodegroup(s). The number of nodes executing a query may change by (a) changing a compute-nodegroup, or (b) adding or removing nodes from a compute nodegroup; and/or distributing data to the storage nodegroup based on a Distribution Method which may be specified by a Distribution Vector (DV) that determines at least where each row is stored.

A database management system implemented in a cloud computing environment. Operational nodes are assigned as controller-nodes, compute-nodes or storage-nodes. The number of operational nodes, and their assignment as compute-nodes or storage-nodes can vary. Queries specify tables, with each such table assigned to a respective group of storage nodes. The number of operational nodes executing a given query may change by (a) changing the compute-nodegroup associated with a connection, or (b) adding or removing nodes from the compute-nodegroup; and/or distributing data from the tables among the nodes in a storage nodegroup. State information is maintained for each client connection, and recorded for a given connection, so that subsequent steps from the same connection are executed with the state as left by a prior step, and so that subsequent queries on the same connection are executed with the state as left by the prior query.

Process architecture for elastic stateful shared nothing system

A database management system implemented in a cloud computing environment. Operational nodes are assigned as groups of controller-nodes, compute-nodes or storage-nodes. Queries specify one or more tables for an associated database operation, with each table being assigned to respective storage nodegroup(s). The number of nodes executing a given query may change, by (a) changing the compute-nodes associated with a connection, or (b) adding or removing nodes associated with a connection; and/or distributing data to a storage nodegroup based on a Distribution Method which may be either data dependent or data independent. A controller node further executes a Dynamic Query Planner (DQP) process that develops a query plan.

Growing community of inventors

Bolton, MA, United States of America

Mrithyunjaya Annapragada