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US Patent 10031956 Aggregation framework system architecture and method

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Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10031956
Date of Patent
July 24, 2018
Patent Application Number
15042297
Date Filed
February 12, 2016
Patent Citations Received
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US Patent 11403317 Aggregation framework system architecture and method
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US Patent 11288282 Distributed database systems and methods with pluggable storage engines
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US Patent 11394532 Systems and methods for hierarchical key management in encrypted distributed databases
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US Patent 11481289 Method and apparatus for reading and writing committed data
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US Patent 10262050 Distributed database systems and methods with pluggable storage engines
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US Patent 11520670 Method and apparatus for restoring data from snapshots
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US Patent 10346430 System and method for determining consensus within a distributed database
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US Patent 10366100 Aggregation framework system architecture and method
...
Patent Primary Examiner
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Frantz Coby
Patent abstract

Database systems and methods that implement a data aggregation framework are provided. The framework can be configured to optimize aggregate operations over non-relational distributed databases, including, for example, data access, data retrieval, data writes, indexing, etc. Various embodiments are configured to aggregate multiple operations and/or commands, where the results (e.g., database documents and computations) captured from the distributed database are transformed as they pass through an aggregation operation. The aggregation operation can be defined as a pipeline which enables the results from a first operation to be redirected into the input of a subsequent operation, which output can be redirected into further subsequent operations. Computations may also be executed at each stage of the pipeline, where each result at each stage can be evaluated by the computation to return a result. Execution of the pipeline can be optimized based on data dependencies and re-ordering of the pipeline operations.

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