Architecting a Heterogeneous Data Platform Across Clusters, Regions, and Clouds

TDEA | Alluxio *

Alluxio foresaw the need for agility when accessing data across silos separated from compute engines like Spark, Presto, Tensorflow and PyTorch. Embracing the separation of storage from compute, the Alluxio data orchestration platform simplifies adoption of the data lake and data mesh paradigm for analytics and AI/ML.

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.

Tags: , , , ,

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.

Tags: , , , , ,

Accelerate Analytics and ML in the Hybrid Cloud Era

Alluxio Tech Talk *

In this talk, we will walk through what Alluxio’s Data Orchestration for the hybrid cloud era is and how it solves the performance and data management challenges we see.

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.

Tags: , , , , ,

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.

Tags: , , , , , , ,