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TensorDB : In-Database Tensor Manipulation with Tensor-Relational Query Plans

TensorDB : In-Database Tensor Manipulation with Tensor-Relational Query Plans. Mijung Kim and K. Selçuk Candan Arizona State University. TensorDB : The Need for it. Today’s data management systems need to support: relational-algebraic operations (for data manipulation and integration )

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TensorDB : In-Database Tensor Manipulation with Tensor-Relational Query Plans

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  1. TensorDB: In-Database Tensor Manipulation with Tensor-Relational Query Plans Mijung Kim and K. SelçukCandan Arizona State University

  2. TensorDB: The Need for it • Today’s data management systems need to support: • relational-algebraic operations (for data manipulation and integration) • tensor-algebraic operations (for analysis) and • As today’s data gets larger, to support a tensor model and tensor algorithms for data analysis, the MATLAB-based in-memory implementations are limited!

  3. TensorDB • An in-database analytic system • for efficient implementations of in-database tensor decompositions on chunk-based array data stores • supports tensor-relational query plans of tensor decomposition operations, along with the relational operations such as selection and join operations

  4. System Demonstration Video

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