Deep Lake, a Lakehouse for Deep Learning: Deep Lake System Overview

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Researchers introduce Deep Lake, an open-source lakehouse for deep learning, optimizing complex data storage and streaming for deep learning frameworks.

Authors: Sasun Hambardzumyan, Activeloop, Mountain View, CA, USA; Abhinav Tuli, Activeloop, Mountain View, CA, USA; Levon Ghukasyan, Activeloop, Mountain View, CA, USA; Fariz Rahman, Activeloop, Mountain View, CA, USA;.

As shown in Fig. 1, Deep Lake stores raw data and views in object storage such as S3 and materializes datasets with full lineage. Streaming, Tensor Query Language queries, and Visualization engine execute along with either deep learning compute or on the browser without requiring external managed or centralized service. 4.1 Ingestion 4.1.1 Extract. Sometimes metadata might already reside in a relational database. We additionally built an ETL destination connector using Airbyte .

As shown in Fig. 1, Deep Lake stores raw data and views in object storage such as S3 and materializes datasets with full lineage. Streaming, Tensor Query Language queries, and Visualization engine execute along with either deep learning compute or on the browser without requiring external managed or centralized service. 4.1 Ingestion 4.1.1 Extract. Sometimes metadata might already reside in a relational database. We additionally built an ETL destination connector using Airbyte .

 

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