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.

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.

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.

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.

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.

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.

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.

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.