Mar 23, 20222 min
Alluxio, the developer of the open-source data orchestration platform for data-driven workloads such as large-scale analytics and AI/ML, has announced the integration of NetApp StorageGRID, software-defined scalable object storage for distributed data with security and disaster recovery, with Alluxio’s Data Orchestration Platform that simplifies the delivery of data to a wide variety of data-driven applications. The combined solution helps enterprises accelerate the adoption of the cloud and optimize their resource spend for a modern data platform ready for enormous scale.
Large enterprises have myriad data-driven applications with complex dependencies and data platforms that span multiple regions across a private, public, or hybrid multi-cloud. The joint solution addresses two key aspects for such a platform: storing data and serving data across geographical regions. A wide range of use cases across industries benefit from the joint solution with the agility needed to cater to evolving requirements, avoiding data silos across business units and optimizing storage cost while maximizing performance.
“NetApp StorageGRID promises to provide reliable storage for analytics and AI solutions spanning regions for some of our largest customers,” said Adit Madan, Sr. Product Manager, Alluxio. “This joint solution will help data platform teams architect for a hybrid and multi-cloud strategy, manage capacity for overloaded analytics infrastructure or expand their usage of a modern data platform for additional analytics and ML.”
“More and more, enterprise applications and workloads span across growing hybrid multi-cloud environments, and as such organizations face increasing complexity to manage business-critical data,” said Duncan Moore, General Manager, Object Storage at NetApp. “These enterprises require simple, robust and reliable solutions to meet their needs. With Alluxio, we’re accelerating the adoption of NetApp StorageGRID to new workloads and architectures and delivering an enterprise-grade data management solution for analytic workloads on on-premises object stores.”
Data platform teams using engines like Presto, Spark, PyTorch, and TensorFlow will benefit from the joint solution for all data storage and management needs when data is segregated across regions for load balancing or high availability. Key highlights of the joint integration include:
Unified Namespace to Break Down Data Silos. The solution provides a unified view of data spread across regions for agility across applications.
Transparent Data Tiering. Hot and cold data is managed across expensive and cheaper storage tiers transparently to applications with a single data management interface.
Data Caching Across Regions. The solution maximizes data availability for compute spread across regions while optimizing space utilization.