Accelerate and Scale Big Data Analytics and Machine Learning Pipelines with Disaggregated Compute and Storage
Recorded: Wednesday, May 2, 2019
The ever increasing challenge to process and extract value from exploding data with AI and analytics workloads makes a memory centric architecture with disaggregated storage and compute more attractive. This decoupled architecture enables users to innovate faster and scale on-demand. Companies can scale their storage capacity to match the rate of their data growth, independent of compute and vice versa.
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Enterprises are increasingly looking towards object stores to power their big data & machine learning workloads in a cost-effective way. The combination of SwiftStack and Alluxio together, enables users to seamlessly move towards a disaggregated architecture. Swiftstack provides a massively parallel cloud object storage and multi-cloud data management system. Alluxio is a data orchestration layer, which sits between compute frameworks and storage systems and enables big data workloads to be deployed directly on SwiftStack. Alluxio provides data locality, accessibility and elasticity via its core innovations. With the Alluxio and Swiftstack solution, Spark, Presto, Tensorflow and Hive and other compute workloads can benefit from 10X performance improvement and dramatically lower costs. In this webinar, we will provide a brief overview of the Alluxio and SwiftStack solution as well as the key use cases it enables.
|Shailesh Manjrekar SwiftStack Head of AI/ML Product & Solutions|
|Dipti Borkar Alluxio Head of Product|