This article highlights synergy between the two widely adopted open-source projects, Alluxio and Presto, and demonstrates how together they deliver a self-serve data architecture across clouds.
Data platform teams are increasingly challenged with accessing multiple data stores that are separated from compute engines, such as Spark, Presto, TensorFlow or PyTorch. Whether your data is distributed across multiple datacenters and/or clouds, a successful heterogeneous data platform requires efficient data access. Alluxio enables you to embrace the separation of storage from compute and use Alluxio data orchestration to simplify adoption of the data lake and data mesh paradigms for analytics and AI/ML workloads.
Tags: ai, analytics, cloud, compute, data orchestration, data platform, data stores, ml, storage
Whether your data is distributed across multiple datacenters and/or clouds, a successful heterogeneous data platform requires efficient data access. Alluxio enables you to embrace the separation of storage from compute and use Alluxio data orchestration to simplify adoption of the data lake and data mesh paradigms for analytics and AI/ML workloads.
Alluxio is a leading data orchestration platform that offers a compute agnostic, storage agnostic, and cloud agnostic solution for big data and machine learning applications. Aunalytics is a data platform company delivering Insights-as-a-Service to answer enterprise and mid-sized companies’ most important IT and business questions.
Tags: aunalytics, big data, cloud, compute, data orchestration, machine learning, storage
In this talk, we will present how using Alluxio computation and storage ecosystems can better interact benefiting of the “bringing the data close to the code” approach. Moving away from the complete disaggregation of computation and storage, data locality can enhance the computation performance. During this talk, we will present our observations and testing results that will show important enhancements in accelerating Spark Data Analytics on Ceph Objects Storage using Alluxio.
Tags: ceph, compute, data orchestration, data orchestration summit, spark, storage
In this talk, we will present how using Alluxio computation and storage ecosystems can better interact benefiting the “bringing the data close to the code” approach. Moving away from the complete disaggregation of computation and storage, data locality can enhance the computation performance. During this talk, we will present our observations and testing results that will show important enhancements in accelerating Spark Data Analytics on Ceph Objects Storage using Alluxio.
Tags: ceph, compute, data locality, distributed storage, meetup, object storage, storage
In this office hour, we demonstrate how a “zero-copy burst” solution helps to speed up Spark and Presto queries in the public cloud while eliminating the process of manually copying and synchronizing data from the on-premise data lake to cloud storage. This approach allows compute frameworks to decouple from on-premise data sources and scale efficiently by leveraging Alluxio and public cloud resources such as AWS.
Tags: aws, cloud storage, compute, hdfs, hybrid cloud, office hour, performance, presto, spark, zero copy bursting
In this office hour, we demonstrate how a “zero-copy burst” solution helps to speed up Spark and Presto queries in the public cloud while eliminating the process of manually copying and synchronizing data from the on-premise data lake to cloud storage. This approach allows compute frameworks to decouple from on-premise data sources and scale efficiently by leveraging Alluxio and public cloud resources such as AWS.
In this tech talk, we’ll discuss why DBS turned to Alluxio’s bursting approach to help solve on-prem compute capacity challenges.