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SAVIME: An Array DBMS for Simulation Analysis and ML Models Prediction

SAVIME: An Array DBMS for Simulation Analysis and ML Models Prediction

14/02/2021
Authors
Hermano. L. S. Lustosa, Anderson C. Silva, Daniel N. R. da Silva, Patrick Valduriez, Fabio Porto

Limitations in current DBMSs prevent their wide adoption in scientific applications. In order to make them benefit from DBMS support, enabling Declarative data analysis and visualization over scientific data, we present an in-memory array DBMS system called SAVIME. In this work we describe the system SAVIME, along with its data model. Our preliminary evaluation show how SAVIME, by using a simple storage definition language (SDL) can outperform the state-of-the-art array database system, SciDB, during the process of data ingestion. We also show that it is possible to use SAVIME as a storage alternative for a numerical solver without affecting its scalability, making it useful for modern ML based applications.

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Dexl Members

Fabio Porto
Hermano Lourenço Souza Lustosa
Anderson Chaves da Silva
Daniel N. Ramos da Silva

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