Accelerate Analytics and ML in the Hybrid Cloud Era

Many companies we talk to have on premises data lakes and use the cloud(s) to burst compute. Many are now establishing new object data lakes as well. As a result, running analytics such as Hive, Spark, Presto and machine learning are experiencing sluggish response times with data and compute in multiple locations. We also know there is an immense and growing data management burden to support these workflows.

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Accelerate Analytics and ML in the Hybrid Cloud Era

Many companies we talk to have on premises data lakes and use the cloud(s) to burst compute. Many are now establishing new object data lakes as well. As a result, running analytics such as Hive, Spark, Presto and machine learning are experiencing sluggish response times with data and compute in multiple locations. We also know there is an immense and growing data management burden to support these workflows.

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Enabling Hybrid Cloud Analytics and AI with Data Orchestration

IoT World Today Webinar *

Adit Madan and Parviz Peiravi offer an overview of the Alluxio data orchestration layer that provides a unified data access layer for hybrid and multi cloud deployments, leveraging Intel® Optane™ Persistent Memory for higher performance caching at reduced cost. The data access layer enables distributed compute engines like Presto, TensorFlow, and PyTorch to transparently access data from various storage systems (including S3, HDFS, and Azure) while actively leveraging a multi-tier cache to accelerate data access.

Unify Data Analytics: Any Stack Any Cloud | Webinar | Big Data Demystified

Alluxio Tech Talk *

This webinar reviews: The observation and analysis of trends of separation of Storage and Compute in Big Data ecosystem; Why and how to build a new data access layer between compute and storage in this data stack; Alluxio open source: history, overview, design, and architecture; Production Use case with Spark, Presto, Tensorflow and etc; A demo of running Presto on Alluxio on S3