Blog
Alluxio's strong Q2 featured Enterprise AI 3.7 launch with sub-millisecond latency (45× faster than S3 Standard), 50%+ customer growth including Salesforce and Geely, and MLPerf Storage v2.0 results showing 99%+ GPU utilization, positioning the company as a leader in maximizing AI infrastructure ROI.
In this blog, Greg Lindstrom, Vice President of ML Trading at Blackout Power Trading, an electricity trading firm in North American power markets, shares how they leverage Alluxio to power their offline feature store. This approach delivers multi-join query performance in the double-digit millisecond range, while maintaining the cost and durability benefits of Amazon S3 for persistent storage. As a result, they achieved a 22 to 37x reduction in large-join query latency for training and a 37 to 83x reduction in large-join query latency for inference.
.png)
.jpeg)
Modern analytics projects rely on a hodgepodge of compute clusters, data stores, and pipelines, flung across countries and continents. Enterprises struggle to meet performance SLAs without replicating lots of data or moving and re-coding applications.
.jpeg)
.jpeg)
The problem with data modernization initiatives is that they result in distributed datasets that impede analytics projects. As enterprises start their cloud migration journey, adopt new types of applications, data stores, and infrastructure, they still leave residual data in the original location. This results in far-flung silos that can be slow, complex and expensive to analyze. As business demands for analytics rise—along with cloud costs—enterprises need to rationalize how they access and process distributed data. They cannot afford to replicate entire datasets or rewrite software every time they study data in more than one location.
.jpeg)
.jpeg)
Xi Chen, Senior Software Engineer at Tencent & Top 100 Alluxio open source project contributor, explains the block allocation policy of Alluxio at the code level.
This blog was originally published on the website of NetApp: https://www.netapp.com/blog/modernize-analytics-workloads-netapp-alluxio/
Imagine as an IT leader having the flexibility to choose any services that are available in public cloud and on premises. And imagine being able to scale your storage for your data lakes with control over data locality and protection for your organization. With these goals in mind, NetApp and Alluxio are joining forces to help our customers adapt to new requirements for modernizing data architecture with low-touch operations for analytics, machine learning, and artificial intelligence workflows.